--- _id: '5945' abstract: - lang: eng text: In developing organisms, spatially prescribed cell identities are thought to be determined by the expression levels of multiple genes. Quantitative tests of this idea, however, require a theoretical framework capable of exposing the rules and precision of cell specification over developmental time. We use the gap gene network in the early fly embryo as an example to show how expression levels of the four gap genes can be jointly decoded into an optimal specification of position with 1% accuracy. The decoder correctly predicts, with no free parameters, the dynamics of pair-rule expression patterns at different developmental time points and in various mutant backgrounds. Precise cellular identities are thus available at the earliest stages of development, contrasting the prevailing view of positional information being slowly refined across successive layers of the patterning network. Our results suggest that developmental enhancers closely approximate a mathematically optimal decoding strategy. article_processing_charge: No article_type: original author: - first_name: Mariela D. full_name: Petkova, Mariela D. last_name: Petkova - first_name: Gasper full_name: Tkacik, Gasper id: 3D494DCA-F248-11E8-B48F-1D18A9856A87 last_name: Tkacik orcid: 0000-0002-6699-1455 - first_name: William full_name: Bialek, William last_name: Bialek - first_name: Eric F. full_name: Wieschaus, Eric F. last_name: Wieschaus - first_name: Thomas full_name: Gregor, Thomas last_name: Gregor citation: ama: Petkova MD, Tkačik G, Bialek W, Wieschaus EF, Gregor T. Optimal decoding of cellular identities in a genetic network. Cell. 2019;176(4):844-855.e15. doi:10.1016/j.cell.2019.01.007 apa: Petkova, M. D., Tkačik, G., Bialek, W., Wieschaus, E. F., & Gregor, T. (2019). Optimal decoding of cellular identities in a genetic network. Cell. Cell Press. https://doi.org/10.1016/j.cell.2019.01.007 chicago: Petkova, Mariela D., Gašper Tkačik, William Bialek, Eric F. Wieschaus, and Thomas Gregor. “Optimal Decoding of Cellular Identities in a Genetic Network.” Cell. Cell Press, 2019. https://doi.org/10.1016/j.cell.2019.01.007. ieee: M. D. Petkova, G. Tkačik, W. Bialek, E. F. Wieschaus, and T. Gregor, “Optimal decoding of cellular identities in a genetic network,” Cell, vol. 176, no. 4. Cell Press, p. 844–855.e15, 2019. ista: Petkova MD, Tkačik G, Bialek W, Wieschaus EF, Gregor T. 2019. Optimal decoding of cellular identities in a genetic network. Cell. 176(4), 844–855.e15. mla: Petkova, Mariela D., et al. “Optimal Decoding of Cellular Identities in a Genetic Network.” Cell, vol. 176, no. 4, Cell Press, 2019, p. 844–855.e15, doi:10.1016/j.cell.2019.01.007. short: M.D. Petkova, G. Tkačik, W. Bialek, E.F. Wieschaus, T. Gregor, Cell 176 (2019) 844–855.e15. date_created: 2019-02-10T22:59:16Z date_published: 2019-02-07T00:00:00Z date_updated: 2023-08-24T14:42:47Z day: '07' department: - _id: GaTk doi: 10.1016/j.cell.2019.01.007 external_id: isi: - '000457969200015' pmid: - '30712870' intvolume: ' 176' isi: 1 issue: '4' language: - iso: eng main_file_link: - open_access: '1' url: https://doi.org/10.1016/j.cell.2019.01.007 month: '02' oa: 1 oa_version: Published Version page: 844-855.e15 pmid: 1 project: - _id: 254E9036-B435-11E9-9278-68D0E5697425 call_identifier: FWF grant_number: P28844-B27 name: Biophysics of information processing in gene regulation publication: Cell publication_status: published publisher: Cell Press quality_controlled: '1' related_material: link: - description: News on IST Homepage relation: press_release url: https://ist.ac.at/en/news/cells-find-their-identity-using-a-mathematically-optimal-strategy/ scopus_import: '1' status: public title: Optimal decoding of cellular identities in a genetic network type: journal_article user_id: 4359f0d1-fa6c-11eb-b949-802e58b17ae8 volume: 176 year: '2019' ... --- _id: '6049' abstract: - lang: eng text: 'In this article it is shown that large systems with many interacting units endowing multiple phases display self-oscillations in the presence of linear feedback between the control and order parameters, where an Andronov–Hopf bifurcation takes over the phase transition. This is simply illustrated through the mean field Landau theory whose feedback dynamics turn out to be described by the Van der Pol equation and it is then validated for the fully connected Ising model following heat bath dynamics. Despite its simplicity, this theory accounts potentially for a rich range of phenomena: here it is applied to describe in a stylized way (i) excess demand-price cycles due to strong herding in a simple agent-based market model; (ii) congestion waves in queuing networks triggered by user feedback to delays in overloaded conditions; and (iii) metabolic network oscillations resulting from cell growth control in a bistable phenotypic landscape.' article_number: '045002' article_processing_charge: Yes (in subscription journal) author: - first_name: Daniele full_name: De Martino, Daniele id: 3FF5848A-F248-11E8-B48F-1D18A9856A87 last_name: De Martino orcid: 0000-0002-5214-4706 citation: ama: 'De Martino D. Feedback-induced self-oscillations in large interacting systems subjected to phase transitions. Journal of Physics A: Mathematical and Theoretical. 2019;52(4). doi:10.1088/1751-8121/aaf2dd' apa: 'De Martino, D. (2019). Feedback-induced self-oscillations in large interacting systems subjected to phase transitions. Journal of Physics A: Mathematical and Theoretical. IOP Publishing. https://doi.org/10.1088/1751-8121/aaf2dd' chicago: 'De Martino, Daniele. “Feedback-Induced Self-Oscillations in Large Interacting Systems Subjected to Phase Transitions.” Journal of Physics A: Mathematical and Theoretical. IOP Publishing, 2019. https://doi.org/10.1088/1751-8121/aaf2dd.' ieee: 'D. De Martino, “Feedback-induced self-oscillations in large interacting systems subjected to phase transitions,” Journal of Physics A: Mathematical and Theoretical, vol. 52, no. 4. IOP Publishing, 2019.' ista: 'De Martino D. 2019. Feedback-induced self-oscillations in large interacting systems subjected to phase transitions. Journal of Physics A: Mathematical and Theoretical. 52(4), 045002.' mla: 'De Martino, Daniele. “Feedback-Induced Self-Oscillations in Large Interacting Systems Subjected to Phase Transitions.” Journal of Physics A: Mathematical and Theoretical, vol. 52, no. 4, 045002, IOP Publishing, 2019, doi:10.1088/1751-8121/aaf2dd.' short: 'D. De Martino, Journal of Physics A: Mathematical and Theoretical 52 (2019).' date_created: 2019-02-24T22:59:19Z date_published: 2019-01-07T00:00:00Z date_updated: 2023-08-24T14:49:23Z day: '07' ddc: - '570' department: - _id: GaTk doi: 10.1088/1751-8121/aaf2dd ec_funded: 1 external_id: isi: - '000455379500001' file: - access_level: open_access checksum: 1112304ad363a6d8afaeccece36473cf content_type: application/pdf creator: kschuh date_created: 2019-04-19T12:18:57Z date_updated: 2020-07-14T12:47:17Z file_id: '6344' file_name: 2019_IOP_DeMartino.pdf file_size: 1804557 relation: main_file file_date_updated: 2020-07-14T12:47:17Z has_accepted_license: '1' intvolume: ' 52' isi: 1 issue: '4' language: - iso: eng license: https://creativecommons.org/licenses/by/4.0/ month: '01' oa: 1 oa_version: Published Version project: - _id: 25681D80-B435-11E9-9278-68D0E5697425 call_identifier: FP7 grant_number: '291734' name: International IST Postdoc Fellowship Programme publication: 'Journal of Physics A: Mathematical and Theoretical' publication_status: published publisher: IOP Publishing quality_controlled: '1' scopus_import: '1' status: public title: Feedback-induced self-oscillations in large interacting systems subjected to phase transitions tmp: image: /images/cc_by.png legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0) short: CC BY (4.0) type: journal_article user_id: 4359f0d1-fa6c-11eb-b949-802e58b17ae8 volume: 52 year: '2019' ... --- _id: '6046' abstract: - lang: eng text: Sudden stress often triggers diverse, temporally structured gene expression responses in microbes, but it is largely unknown how variable in time such responses are and if genes respond in the same temporal order in every single cell. Here, we quantified timing variability of individual promoters responding to sublethal antibiotic stress using fluorescent reporters, microfluidics, and time‐lapse microscopy. We identified lower and upper bounds that put definite constraints on timing variability, which varies strongly among promoters and conditions. Timing variability can be interpreted using results from statistical kinetics, which enable us to estimate the number of rate‐limiting molecular steps underlying different responses. We found that just a few critical steps control some responses while others rely on dozens of steps. To probe connections between different stress responses, we then tracked the temporal order and response time correlations of promoter pairs in individual cells. Our results support that, when bacteria are exposed to the antibiotic nitrofurantoin, the ensuing oxidative stress and SOS responses are part of the same causal chain of molecular events. In contrast, under trimethoprim, the acid stress response and the SOS response are part of different chains of events running in parallel. Our approach reveals fundamental constraints on gene expression timing and provides new insights into the molecular events that underlie the timing of stress responses. acknowledged_ssus: - _id: Bio article_number: e8470 article_processing_charge: No author: - first_name: Karin full_name: Mitosch, Karin id: 39B66846-F248-11E8-B48F-1D18A9856A87 last_name: Mitosch - first_name: Georg full_name: Rieckh, Georg id: 34DA8BD6-F248-11E8-B48F-1D18A9856A87 last_name: Rieckh - first_name: Mark Tobias full_name: Bollenbach, Mark Tobias id: 3E6DB97A-F248-11E8-B48F-1D18A9856A87 last_name: Bollenbach orcid: 0000-0003-4398-476X citation: ama: Mitosch K, Rieckh G, Bollenbach MT. Temporal order and precision of complex stress responses in individual bacteria. Molecular systems biology. 2019;15(2). doi:10.15252/msb.20188470 apa: Mitosch, K., Rieckh, G., & Bollenbach, M. T. (2019). Temporal order and precision of complex stress responses in individual bacteria. Molecular Systems Biology. Embo Press. https://doi.org/10.15252/msb.20188470 chicago: Mitosch, Karin, Georg Rieckh, and Mark Tobias Bollenbach. “Temporal Order and Precision of Complex Stress Responses in Individual Bacteria.” Molecular Systems Biology. Embo Press, 2019. https://doi.org/10.15252/msb.20188470. ieee: K. Mitosch, G. Rieckh, and M. T. Bollenbach, “Temporal order and precision of complex stress responses in individual bacteria,” Molecular systems biology, vol. 15, no. 2. Embo Press, 2019. ista: Mitosch K, Rieckh G, Bollenbach MT. 2019. Temporal order and precision of complex stress responses in individual bacteria. Molecular systems biology. 15(2), e8470. mla: Mitosch, Karin, et al. “Temporal Order and Precision of Complex Stress Responses in Individual Bacteria.” Molecular Systems Biology, vol. 15, no. 2, e8470, Embo Press, 2019, doi:10.15252/msb.20188470. short: K. Mitosch, G. Rieckh, M.T. Bollenbach, Molecular Systems Biology 15 (2019). date_created: 2019-02-24T22:59:18Z date_published: 2019-02-14T00:00:00Z date_updated: 2023-08-24T14:49:53Z day: '14' department: - _id: GaTk doi: 10.15252/msb.20188470 external_id: isi: - '000459628300003' pmid: - '30765425' intvolume: ' 15' isi: 1 issue: '2' language: - iso: eng main_file_link: - open_access: '1' url: https://www.ncbi.nlm.nih.gov/pubmed/30765425 month: '02' oa: 1 oa_version: Submitted Version pmid: 1 project: - _id: 25E9AF9E-B435-11E9-9278-68D0E5697425 call_identifier: FWF grant_number: P27201-B22 name: Revealing the mechanisms underlying drug interactions - _id: 25EB3A80-B435-11E9-9278-68D0E5697425 grant_number: RGP0042/2013 name: Revealing the fundamental limits of cell growth publication: Molecular systems biology publication_status: published publisher: Embo Press quality_controlled: '1' scopus_import: '1' status: public title: Temporal order and precision of complex stress responses in individual bacteria type: journal_article user_id: 4359f0d1-fa6c-11eb-b949-802e58b17ae8 volume: 15 year: '2019' ... --- _id: '6784' abstract: - lang: eng text: Mathematical models have been used successfully at diverse scales of biological organization, ranging from ecology and population dynamics to stochastic reaction events occurring between individual molecules in single cells. Generally, many biological processes unfold across multiple scales, with mutations being the best studied example of how stochasticity at the molecular scale can influence outcomes at the population scale. In many other contexts, however, an analogous link between micro- and macro-scale remains elusive, primarily due to the challenges involved in setting up and analyzing multi-scale models. Here, we employ such a model to investigate how stochasticity propagates from individual biochemical reaction events in the bacterial innate immune system to the ecology of bacteria and bacterial viruses. We show analytically how the dynamics of bacterial populations are shaped by the activities of immunity-conferring enzymes in single cells and how the ecological consequences imply optimal bacterial defense strategies against viruses. Our results suggest that bacterial populations in the presence of viruses can either optimize their initial growth rate or their population size, with the first strategy favoring simple immunity featuring a single restriction modification system and the second strategy favoring complex bacterial innate immunity featuring several simultaneously active restriction modification systems. article_number: e1007168 article_processing_charge: No article_type: original author: - first_name: Jakob full_name: Ruess, Jakob id: 4A245D00-F248-11E8-B48F-1D18A9856A87 last_name: Ruess orcid: 0000-0003-1615-3282 - first_name: Maros full_name: Pleska, Maros id: 4569785E-F248-11E8-B48F-1D18A9856A87 last_name: Pleska orcid: 0000-0001-7460-7479 - first_name: Calin C full_name: Guet, Calin C id: 47F8433E-F248-11E8-B48F-1D18A9856A87 last_name: Guet orcid: 0000-0001-6220-2052 - first_name: Gašper full_name: Tkačik, Gašper id: 3D494DCA-F248-11E8-B48F-1D18A9856A87 last_name: Tkačik orcid: 0000-0002-6699-1455 citation: ama: Ruess J, Pleska M, Guet CC, Tkačik G. Molecular noise of innate immunity shapes bacteria-phage ecologies. PLoS Computational Biology. 2019;15(7). doi:10.1371/journal.pcbi.1007168 apa: Ruess, J., Pleska, M., Guet, C. C., & Tkačik, G. (2019). Molecular noise of innate immunity shapes bacteria-phage ecologies. PLoS Computational Biology. Public Library of Science. https://doi.org/10.1371/journal.pcbi.1007168 chicago: Ruess, Jakob, Maros Pleska, Calin C Guet, and Gašper Tkačik. “Molecular Noise of Innate Immunity Shapes Bacteria-Phage Ecologies.” PLoS Computational Biology. Public Library of Science, 2019. https://doi.org/10.1371/journal.pcbi.1007168. ieee: J. Ruess, M. Pleska, C. C. Guet, and G. Tkačik, “Molecular noise of innate immunity shapes bacteria-phage ecologies,” PLoS Computational Biology, vol. 15, no. 7. Public Library of Science, 2019. ista: Ruess J, Pleska M, Guet CC, Tkačik G. 2019. Molecular noise of innate immunity shapes bacteria-phage ecologies. PLoS Computational Biology. 15(7), e1007168. mla: Ruess, Jakob, et al. “Molecular Noise of Innate Immunity Shapes Bacteria-Phage Ecologies.” PLoS Computational Biology, vol. 15, no. 7, e1007168, Public Library of Science, 2019, doi:10.1371/journal.pcbi.1007168. short: J. Ruess, M. Pleska, C.C. Guet, G. Tkačik, PLoS Computational Biology 15 (2019). date_created: 2019-08-11T21:59:19Z date_published: 2019-07-02T00:00:00Z date_updated: 2023-08-29T07:10:06Z day: '02' ddc: - '570' department: - _id: CaGu - _id: GaTk doi: 10.1371/journal.pcbi.1007168 external_id: isi: - '000481577700032' file: - access_level: open_access checksum: 7ded4721b41c2a0fc66a1c634540416a content_type: application/pdf creator: dernst date_created: 2019-08-12T12:27:26Z date_updated: 2020-07-14T12:47:40Z file_id: '6803' file_name: 2019_PlosComputBiology_Ruess.pdf file_size: 2200003 relation: main_file file_date_updated: 2020-07-14T12:47:40Z has_accepted_license: '1' intvolume: ' 15' isi: 1 issue: '7' language: - iso: eng month: '07' oa: 1 oa_version: Published Version project: - _id: 251D65D8-B435-11E9-9278-68D0E5697425 grant_number: '24210' name: Effects of Stochasticity on the Function of Restriction-Modi cation Systems at the Single-Cell Level - _id: 251BCBEC-B435-11E9-9278-68D0E5697425 grant_number: RGY0079/2011 name: Multi-Level Conflicts in Evolutionary Dynamics of Restriction-Modification Systems publication: PLoS Computational Biology publication_identifier: eissn: - 1553-7358 publication_status: published publisher: Public Library of Science quality_controlled: '1' related_material: record: - id: '9786' relation: research_data status: public scopus_import: '1' status: public title: Molecular noise of innate immunity shapes bacteria-phage ecologies tmp: image: /images/cc_by.png legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0) short: CC BY (4.0) type: journal_article user_id: 4359f0d1-fa6c-11eb-b949-802e58b17ae8 volume: 15 year: '2019' ... --- _id: '9786' article_processing_charge: No author: - first_name: Jakob full_name: Ruess, Jakob id: 4A245D00-F248-11E8-B48F-1D18A9856A87 last_name: Ruess orcid: 0000-0003-1615-3282 - first_name: Maros full_name: Pleska, Maros id: 4569785E-F248-11E8-B48F-1D18A9856A87 last_name: Pleska orcid: 0000-0001-7460-7479 - first_name: Calin C full_name: Guet, Calin C id: 47F8433E-F248-11E8-B48F-1D18A9856A87 last_name: Guet orcid: 0000-0001-6220-2052 - first_name: Gašper full_name: Tkačik, Gašper id: 3D494DCA-F248-11E8-B48F-1D18A9856A87 last_name: Tkačik orcid: 0000-0002-6699-1455 citation: ama: Ruess J, Pleska M, Guet CC, Tkačik G. Supporting text and results. 2019. doi:10.1371/journal.pcbi.1007168.s001 apa: Ruess, J., Pleska, M., Guet, C. C., & Tkačik, G. (2019). Supporting text and results. Public Library of Science. https://doi.org/10.1371/journal.pcbi.1007168.s001 chicago: Ruess, Jakob, Maros Pleska, Calin C Guet, and Gašper Tkačik. “Supporting Text and Results.” Public Library of Science, 2019. https://doi.org/10.1371/journal.pcbi.1007168.s001. ieee: J. Ruess, M. Pleska, C. C. Guet, and G. Tkačik, “Supporting text and results.” Public Library of Science, 2019. ista: Ruess J, Pleska M, Guet CC, Tkačik G. 2019. Supporting text and results, Public Library of Science, 10.1371/journal.pcbi.1007168.s001. mla: Ruess, Jakob, et al. Supporting Text and Results. Public Library of Science, 2019, doi:10.1371/journal.pcbi.1007168.s001. short: J. Ruess, M. Pleska, C.C. Guet, G. Tkačik, (2019). date_created: 2021-08-06T08:23:43Z date_published: 2019-07-02T00:00:00Z date_updated: 2023-08-29T07:10:05Z day: '02' department: - _id: CaGu - _id: GaTk doi: 10.1371/journal.pcbi.1007168.s001 month: '07' oa_version: Published Version publisher: Public Library of Science related_material: record: - id: '6784' relation: used_in_publication status: public status: public title: Supporting text and results type: research_data_reference user_id: 6785fbc1-c503-11eb-8a32-93094b40e1cf year: '2019' ... --- _id: '7422' abstract: - lang: eng text: Biochemical reactions often occur at low copy numbers but at once in crowded and diverse environments. Space and stochasticity therefore play an essential role in biochemical networks. Spatial-stochastic simulations have become a prominent tool for understanding how stochasticity at the microscopic level influences the macroscopic behavior of such systems. While particle-based models guarantee the level of detail necessary to accurately describe the microscopic dynamics at very low copy numbers, the algorithms used to simulate them typically imply trade-offs between computational efficiency and biochemical accuracy. eGFRD (enhanced Green’s Function Reaction Dynamics) is an exact algorithm that evades such trade-offs by partitioning the N-particle system into M ≤ N analytically tractable one- and two-particle systems; the analytical solutions (Green’s functions) then are used to implement an event-driven particle-based scheme that allows particles to make large jumps in time and space while retaining access to their state variables at arbitrary simulation times. Here we present “eGFRD2,” a new eGFRD version that implements the principle of eGFRD in all dimensions, thus enabling efficient particle-based simulation of biochemical reaction-diffusion processes in the 3D cytoplasm, on 2D planes representing membranes, and on 1D elongated cylinders representative of, e.g., cytoskeletal tracks or DNA; in 1D, it also incorporates convective motion used to model active transport. We find that, for low particle densities, eGFRD2 is up to 6 orders of magnitude faster than conventional Brownian dynamics. We exemplify the capabilities of eGFRD2 by simulating an idealized model of Pom1 gradient formation, which involves 3D diffusion, active transport on microtubules, and autophosphorylation on the membrane, confirming recent experimental and theoretical results on this system to hold under genuinely stochastic conditions. article_number: '054108' article_processing_charge: No article_type: original author: - first_name: Thomas R full_name: Sokolowski, Thomas R id: 3E999752-F248-11E8-B48F-1D18A9856A87 last_name: Sokolowski orcid: 0000-0002-1287-3779 - first_name: Joris full_name: Paijmans, Joris last_name: Paijmans - first_name: Laurens full_name: Bossen, Laurens last_name: Bossen - first_name: Thomas full_name: Miedema, Thomas last_name: Miedema - first_name: Martijn full_name: Wehrens, Martijn last_name: Wehrens - first_name: Nils B. full_name: Becker, Nils B. last_name: Becker - first_name: Kazunari full_name: Kaizu, Kazunari last_name: Kaizu - first_name: Koichi full_name: Takahashi, Koichi last_name: Takahashi - first_name: Marileen full_name: Dogterom, Marileen last_name: Dogterom - first_name: Pieter Rein full_name: ten Wolde, Pieter Rein last_name: ten Wolde citation: ama: Sokolowski TR, Paijmans J, Bossen L, et al. eGFRD in all dimensions. The Journal of Chemical Physics. 2019;150(5). doi:10.1063/1.5064867 apa: Sokolowski, T. R., Paijmans, J., Bossen, L., Miedema, T., Wehrens, M., Becker, N. B., … ten Wolde, P. R. (2019). eGFRD in all dimensions. The Journal of Chemical Physics. AIP Publishing. https://doi.org/10.1063/1.5064867 chicago: Sokolowski, Thomas R, Joris Paijmans, Laurens Bossen, Thomas Miedema, Martijn Wehrens, Nils B. Becker, Kazunari Kaizu, Koichi Takahashi, Marileen Dogterom, and Pieter Rein ten Wolde. “EGFRD in All Dimensions.” The Journal of Chemical Physics. AIP Publishing, 2019. https://doi.org/10.1063/1.5064867. ieee: T. R. Sokolowski et al., “eGFRD in all dimensions,” The Journal of Chemical Physics, vol. 150, no. 5. AIP Publishing, 2019. ista: Sokolowski TR, Paijmans J, Bossen L, Miedema T, Wehrens M, Becker NB, Kaizu K, Takahashi K, Dogterom M, ten Wolde PR. 2019. eGFRD in all dimensions. The Journal of Chemical Physics. 150(5), 054108. mla: Sokolowski, Thomas R., et al. “EGFRD in All Dimensions.” The Journal of Chemical Physics, vol. 150, no. 5, 054108, AIP Publishing, 2019, doi:10.1063/1.5064867. short: T.R. Sokolowski, J. Paijmans, L. Bossen, T. Miedema, M. Wehrens, N.B. Becker, K. Kaizu, K. Takahashi, M. Dogterom, P.R. ten Wolde, The Journal of Chemical Physics 150 (2019). date_created: 2020-01-30T10:34:36Z date_published: 2019-02-07T00:00:00Z date_updated: 2023-09-06T14:59:28Z day: '07' department: - _id: GaTk doi: 10.1063/1.5064867 external_id: arxiv: - '1708.09364' isi: - '000458109300009' intvolume: ' 150' isi: 1 issue: '5' language: - iso: eng main_file_link: - open_access: '1' url: https://arxiv.org/abs/1708.09364 month: '02' oa: 1 oa_version: Preprint publication: The Journal of Chemical Physics publication_identifier: eissn: - 1089-7690 issn: - 0021-9606 publication_status: published publisher: AIP Publishing quality_controlled: '1' status: public title: eGFRD in all dimensions type: journal_article user_id: c635000d-4b10-11ee-a964-aac5a93f6ac1 volume: 150 year: '2019' ... --- _id: '6900' abstract: - lang: eng text: Across diverse biological systems—ranging from neural networks to intracellular signaling and genetic regulatory networks—the information about changes in the environment is frequently encoded in the full temporal dynamics of the network nodes. A pressing data-analysis challenge has thus been to efficiently estimate the amount of information that these dynamics convey from experimental data. Here we develop and evaluate decoding-based estimation methods to lower bound the mutual information about a finite set of inputs, encoded in single-cell high-dimensional time series data. For biological reaction networks governed by the chemical Master equation, we derive model-based information approximations and analytical upper bounds, against which we benchmark our proposed model-free decoding estimators. In contrast to the frequently-used k-nearest-neighbor estimator, decoding-based estimators robustly extract a large fraction of the available information from high-dimensional trajectories with a realistic number of data samples. We apply these estimators to previously published data on Erk and Ca2+ signaling in mammalian cells and to yeast stress-response, and find that substantial amount of information about environmental state can be encoded by non-trivial response statistics even in stationary signals. We argue that these single-cell, decoding-based information estimates, rather than the commonly-used tests for significant differences between selected population response statistics, provide a proper and unbiased measure for the performance of biological signaling networks. article_processing_charge: No author: - first_name: Sarah A full_name: Cepeda Humerez, Sarah A id: 3DEE19A4-F248-11E8-B48F-1D18A9856A87 last_name: Cepeda Humerez - first_name: Jakob full_name: Ruess, Jakob last_name: Ruess orcid: 0000-0003-1615-3282 - first_name: Gašper full_name: Tkačik, Gašper id: 3D494DCA-F248-11E8-B48F-1D18A9856A87 last_name: Tkačik orcid: 0000-0002-6699-1455 citation: ama: Cepeda Humerez SA, Ruess J, Tkačik G. Estimating information in time-varying signals. PLoS computational biology. 2019;15(9):e1007290. doi:10.1371/journal.pcbi.1007290 apa: Cepeda Humerez, S. A., Ruess, J., & Tkačik, G. (2019). Estimating information in time-varying signals. PLoS Computational Biology. Public Library of Science. https://doi.org/10.1371/journal.pcbi.1007290 chicago: Cepeda Humerez, Sarah A, Jakob Ruess, and Gašper Tkačik. “Estimating Information in Time-Varying Signals.” PLoS Computational Biology. Public Library of Science, 2019. https://doi.org/10.1371/journal.pcbi.1007290. ieee: S. A. Cepeda Humerez, J. Ruess, and G. Tkačik, “Estimating information in time-varying signals,” PLoS computational biology, vol. 15, no. 9. Public Library of Science, p. e1007290, 2019. ista: Cepeda Humerez SA, Ruess J, Tkačik G. 2019. Estimating information in time-varying signals. PLoS computational biology. 15(9), e1007290. mla: Cepeda Humerez, Sarah A., et al. “Estimating Information in Time-Varying Signals.” PLoS Computational Biology, vol. 15, no. 9, Public Library of Science, 2019, p. e1007290, doi:10.1371/journal.pcbi.1007290. short: S.A. Cepeda Humerez, J. Ruess, G. Tkačik, PLoS Computational Biology 15 (2019) e1007290. date_created: 2019-09-22T22:00:37Z date_published: 2019-09-03T00:00:00Z date_updated: 2023-09-07T12:55:21Z day: '03' ddc: - '570' department: - _id: GaTk doi: 10.1371/journal.pcbi.1007290 external_id: isi: - '000489741800021' pmid: - '31479447' file: - access_level: open_access checksum: 81bdce1361c9aa8395d6fa635fb6ab47 content_type: application/pdf creator: kschuh date_created: 2019-10-01T10:53:45Z date_updated: 2020-07-14T12:47:44Z file_id: '6925' file_name: 2019_PLoS_Cepeda-Humerez.pdf file_size: 3081855 relation: main_file file_date_updated: 2020-07-14T12:47:44Z has_accepted_license: '1' intvolume: ' 15' isi: 1 issue: '9' language: - iso: eng month: '09' oa: 1 oa_version: Published Version page: e1007290 pmid: 1 project: - _id: 254E9036-B435-11E9-9278-68D0E5697425 call_identifier: FWF grant_number: P28844-B27 name: Biophysics of information processing in gene regulation publication: PLoS computational biology publication_identifier: eissn: - '15537358' publication_status: published publisher: Public Library of Science quality_controlled: '1' related_material: record: - id: '6473' relation: part_of_dissertation status: public scopus_import: '1' status: public title: Estimating information in time-varying signals tmp: image: /images/cc_by.png legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0) short: CC BY (4.0) type: journal_article user_id: 4359f0d1-fa6c-11eb-b949-802e58b17ae8 volume: 15 year: '2019' ... --- _id: '196' abstract: - lang: eng text: 'The abelian sandpile serves as a model to study self-organized criticality, a phenomenon occurring in biological, physical and social processes. The identity of the abelian group is a fractal composed of self-similar patches, and its limit is subject of extensive collaborative research. Here, we analyze the evolution of the sandpile identity under harmonic fields of different orders. We show that this evolution corresponds to periodic cycles through the abelian group characterized by the smooth transformation and apparent conservation of the patches constituting the identity. The dynamics induced by second and third order harmonics resemble smooth stretchings, respectively translations, of the identity, while the ones induced by fourth order harmonics resemble magnifications and rotations. Starting with order three, the dynamics pass through extended regions of seemingly random configurations which spontaneously reassemble into accentuated patterns. We show that the space of harmonic functions projects to the extended analogue of the sandpile group, thus providing a set of universal coordinates identifying configurations between different domains. Since the original sandpile group is a subgroup of the extended one, this directly implies that it admits a natural renormalization. Furthermore, we show that the harmonic fields can be induced by simple Markov processes, and that the corresponding stochastic dynamics show remarkable robustness over hundreds of periods. Finally, we encode information into seemingly random configurations, and decode this information with an algorithm requiring minimal prior knowledge. Our results suggest that harmonic fields might split the sandpile group into sub-sets showing different critical coefficients, and that it might be possible to extend the fractal structure of the identity beyond the boundaries of its domain. ' acknowledgement: "M.L. is grateful to the members of the C Guet and G Tkacik groups for valuable comments and support. M.S. is grateful to Nikita Kalinin for inspiring communications.\r\n" article_processing_charge: No article_type: original author: - first_name: Moritz full_name: Lang, Moritz id: 29E0800A-F248-11E8-B48F-1D18A9856A87 last_name: Lang - first_name: Mikhail full_name: Shkolnikov, Mikhail id: 35084A62-F248-11E8-B48F-1D18A9856A87 last_name: Shkolnikov orcid: 0000-0002-4310-178X citation: ama: Lang M, Shkolnikov M. Harmonic dynamics of the Abelian sandpile. Proceedings of the National Academy of Sciences. 2019;116(8):2821-2830. doi:10.1073/pnas.1812015116 apa: Lang, M., & Shkolnikov, M. (2019). Harmonic dynamics of the Abelian sandpile. Proceedings of the National Academy of Sciences. National Academy of Sciences. https://doi.org/10.1073/pnas.1812015116 chicago: Lang, Moritz, and Mikhail Shkolnikov. “Harmonic Dynamics of the Abelian Sandpile.” Proceedings of the National Academy of Sciences. National Academy of Sciences, 2019. https://doi.org/10.1073/pnas.1812015116. ieee: M. Lang and M. Shkolnikov, “Harmonic dynamics of the Abelian sandpile,” Proceedings of the National Academy of Sciences, vol. 116, no. 8. National Academy of Sciences, pp. 2821–2830, 2019. ista: Lang M, Shkolnikov M. 2019. Harmonic dynamics of the Abelian sandpile. Proceedings of the National Academy of Sciences. 116(8), 2821–2830. mla: Lang, Moritz, and Mikhail Shkolnikov. “Harmonic Dynamics of the Abelian Sandpile.” Proceedings of the National Academy of Sciences, vol. 116, no. 8, National Academy of Sciences, 2019, pp. 2821–30, doi:10.1073/pnas.1812015116. short: M. Lang, M. Shkolnikov, Proceedings of the National Academy of Sciences 116 (2019) 2821–2830. date_created: 2018-12-11T11:45:08Z date_published: 2019-02-19T00:00:00Z date_updated: 2023-09-11T14:09:34Z day: '19' department: - _id: CaGu - _id: GaTk - _id: TaHa doi: 10.1073/pnas.1812015116 external_id: arxiv: - '1806.10823' isi: - '000459074400013' pmid: - ' 30728300' intvolume: ' 116' isi: 1 issue: '8' language: - iso: eng main_file_link: - open_access: '1' url: https://doi.org/10.1073/pnas.1812015116 month: '02' oa: 1 oa_version: Published Version page: 2821-2830 pmid: 1 publication: Proceedings of the National Academy of Sciences publication_identifier: eissn: - 1091-6490 publication_status: published publisher: National Academy of Sciences quality_controlled: '1' related_material: link: - description: News on IST Webpage relation: press_release url: https://ist.ac.at/en/news/famous-sandpile-model-shown-to-move-like-a-traveling-sand-dune/ scopus_import: '1' status: public title: Harmonic dynamics of the Abelian sandpile type: journal_article user_id: c635000d-4b10-11ee-a964-aac5a93f6ac1 volume: 116 year: '2019' ... --- _id: '5817' abstract: - lang: eng text: We theoretically study the shapes of lipid vesicles confined to a spherical cavity, elaborating a framework based on the so-called limiting shapes constructed from geometrically simple structural elements such as double-membrane walls and edges. Partly inspired by numerical results, the proposed non-compartmentalized and compartmentalized limiting shapes are arranged in the bilayer-couple phase diagram which is then compared to its free-vesicle counterpart. We also compute the area-difference-elasticity phase diagram of the limiting shapes and we use it to interpret shape transitions experimentally observed in vesicles confined within another vesicle. The limiting-shape framework may be generalized to theoretically investigate the structure of certain cell organelles such as the mitochondrion. article_processing_charge: No article_type: original author: - first_name: Bor full_name: Kavcic, Bor id: 350F91D2-F248-11E8-B48F-1D18A9856A87 last_name: Kavcic orcid: 0000-0001-6041-254X - first_name: A. full_name: Sakashita, A. last_name: Sakashita - first_name: H. full_name: Noguchi, H. last_name: Noguchi - first_name: P. full_name: Ziherl, P. last_name: Ziherl citation: ama: Kavcic B, Sakashita A, Noguchi H, Ziherl P. Limiting shapes of confined lipid vesicles. Soft Matter. 2019;15(4):602-614. doi:10.1039/c8sm01956h apa: Kavcic, B., Sakashita, A., Noguchi, H., & Ziherl, P. (2019). Limiting shapes of confined lipid vesicles. Soft Matter. Royal Society of Chemistry. https://doi.org/10.1039/c8sm01956h chicago: Kavcic, Bor, A. Sakashita, H. Noguchi, and P. Ziherl. “Limiting Shapes of Confined Lipid Vesicles.” Soft Matter. Royal Society of Chemistry, 2019. https://doi.org/10.1039/c8sm01956h. ieee: B. Kavcic, A. Sakashita, H. Noguchi, and P. Ziherl, “Limiting shapes of confined lipid vesicles,” Soft Matter, vol. 15, no. 4. Royal Society of Chemistry, pp. 602–614, 2019. ista: Kavcic B, Sakashita A, Noguchi H, Ziherl P. 2019. Limiting shapes of confined lipid vesicles. Soft Matter. 15(4), 602–614. mla: Kavcic, Bor, et al. “Limiting Shapes of Confined Lipid Vesicles.” Soft Matter, vol. 15, no. 4, Royal Society of Chemistry, 2019, pp. 602–14, doi:10.1039/c8sm01956h. short: B. Kavcic, A. Sakashita, H. Noguchi, P. Ziherl, Soft Matter 15 (2019) 602–614. date_created: 2019-01-11T07:37:47Z date_published: 2019-01-10T00:00:00Z date_updated: 2023-09-13T08:47:16Z day: '10' ddc: - '530' department: - _id: GaTk doi: 10.1039/c8sm01956h external_id: isi: - '000457329700003' pmid: - '30629082' file: - access_level: open_access checksum: 614c337d6424ccd3d48d1b1f9513510d content_type: application/pdf creator: bkavcic date_created: 2020-10-09T11:00:05Z date_updated: 2020-10-09T11:00:05Z file_id: '8641' file_name: lmt_sftmtr_V8.pdf file_size: 5370762 relation: main_file success: 1 file_date_updated: 2020-10-09T11:00:05Z has_accepted_license: '1' intvolume: ' 15' isi: 1 issue: '4' language: - iso: eng license: https://creativecommons.org/licenses/by-nc-nd/3.0/ month: '01' oa: 1 oa_version: Submitted Version page: 602-614 pmid: 1 publication: Soft Matter publication_identifier: eissn: - 1744-6848 issn: - 1744-683X publication_status: published publisher: Royal Society of Chemistry quality_controlled: '1' scopus_import: '1' status: public title: Limiting shapes of confined lipid vesicles tmp: image: /images/cc_by_nc_nd.png legal_code_url: https://creativecommons.org/licenses/by-nc-nd/3.0/legalcode name: Creative Commons Attribution-NonCommercial-NoDerivs 3.0 Unported (CC BY-NC-ND 3.0) short: CC BY-NC-ND (3.0) type: journal_article user_id: c635000d-4b10-11ee-a964-aac5a93f6ac1 volume: 15 year: '2019' ... --- _id: '6473' abstract: - lang: eng text: "Single cells are constantly interacting with their environment and each other, more importantly, the accurate perception of environmental cues is crucial for growth, survival, and reproduction. This communication between cells and their environment can be formalized in mathematical terms and be quantified as the information flow between them, as prescribed by information theory. \r\nThe recent availability of real–time dynamical patterns of signaling molecules in single cells has allowed us to identify encoding about the identity of the environment in the time–series. However, efficient estimation of the information transmitted by these signals has been a data–analysis challenge due to the high dimensionality of the trajectories and the limited number of samples. In the first part of this thesis, we develop and evaluate decoding–based estimation methods to lower bound the mutual information and derive model–based precise information estimates for biological reaction networks governed by the chemical master equation. This is followed by applying the decoding-based methods to study the intracellular representation of extracellular changes in budding yeast, by observing the transient dynamics of nuclear translocation of 10 transcription factors in response to 3 stress conditions. Additionally, we apply these estimators to previously published data on ERK and Ca2+ signaling and yeast stress response. We argue that this single cell decoding-based measure of information provides an unbiased, quantitative and interpretable measure for the fidelity of biological signaling processes. \r\nFinally, in the last section, we deal with gene regulation which is primarily controlled by transcription factors (TFs) that bind to the DNA to activate gene expression. The possibility that non-cognate TFs activate transcription diminishes the accuracy of regulation with potentially disastrous effects for the cell. This ’crosstalk’ acts as a previously unexplored source of noise in biochemical networks and puts a strong constraint on their performance. To mitigate erroneous initiation we propose an out of equilibrium scheme that implements kinetic proofreading. We show that such architectures are favored over their equilibrium counterparts for complex organisms despite introducing noise in gene expression. " alternative_title: - ISTA Thesis article_processing_charge: No author: - first_name: Sarah A full_name: Cepeda Humerez, Sarah A id: 3DEE19A4-F248-11E8-B48F-1D18A9856A87 last_name: Cepeda Humerez citation: ama: Cepeda Humerez SA. Estimating information flow in single cells. 2019. doi:10.15479/AT:ISTA:6473 apa: Cepeda Humerez, S. A. (2019). Estimating information flow in single cells. Institute of Science and Technology Austria. https://doi.org/10.15479/AT:ISTA:6473 chicago: Cepeda Humerez, Sarah A. “Estimating Information Flow in Single Cells.” Institute of Science and Technology Austria, 2019. https://doi.org/10.15479/AT:ISTA:6473. ieee: S. A. Cepeda Humerez, “Estimating information flow in single cells,” Institute of Science and Technology Austria, 2019. ista: Cepeda Humerez SA. 2019. Estimating information flow in single cells. Institute of Science and Technology Austria. mla: Cepeda Humerez, Sarah A. Estimating Information Flow in Single Cells. Institute of Science and Technology Austria, 2019, doi:10.15479/AT:ISTA:6473. short: S.A. Cepeda Humerez, Estimating Information Flow in Single Cells, Institute of Science and Technology Austria, 2019. date_created: 2019-05-21T00:11:23Z date_published: 2019-05-23T00:00:00Z date_updated: 2023-09-19T15:13:26Z day: '23' ddc: - '004' degree_awarded: PhD department: - _id: GaTk doi: 10.15479/AT:ISTA:6473 file: - access_level: closed checksum: 75f9184c1346e10a5de5f9cc7338309a content_type: application/zip creator: scepeda date_created: 2019-05-23T11:18:16Z date_updated: 2020-07-14T12:47:31Z file_id: '6480' file_name: Thesis_Cepeda.zip file_size: 23937464 relation: source_file - access_level: open_access checksum: afdc0633ddbd71d5b13550d7fb4f4454 content_type: application/pdf creator: scepeda date_created: 2019-05-23T11:18:13Z date_updated: 2020-07-14T12:47:31Z file_id: '6481' file_name: CepedaThesis.pdf file_size: 16646985 relation: main_file file_date_updated: 2020-07-14T12:47:31Z has_accepted_license: '1' keyword: - Information estimation - Time-series - data analysis language: - iso: eng month: '05' oa: 1 oa_version: Published Version page: '135' publication_identifier: issn: - 2663-337X publication_status: published publisher: Institute of Science and Technology Austria related_material: record: - id: '1576' relation: dissertation_contains status: public - id: '6900' relation: dissertation_contains status: public - id: '281' relation: dissertation_contains status: public - id: '2016' relation: dissertation_contains status: public status: public supervisor: - first_name: Gašper full_name: Tkačik, Gašper id: 3D494DCA-F248-11E8-B48F-1D18A9856A87 last_name: Tkačik orcid: 0000-0002-6699-1455 title: Estimating information flow in single cells tmp: image: /images/cc_by.png legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0) short: CC BY (4.0) type: dissertation user_id: c635000d-4b10-11ee-a964-aac5a93f6ac1 year: '2019' ... --- _id: '6071' abstract: - lang: eng text: 'Transcription factors, by binding to specific sequences on the DNA, control the precise spatio-temporal expression of genes inside a cell. However, this specificity is limited, leading to frequent incorrect binding of transcription factors that might have deleterious consequences on the cell. By constructing a biophysical model of TF-DNA binding in the context of gene regulation, I will first explore how regulatory constraints can strongly shape the distribution of a population in sequence space. Then, by directly linking this to a picture of multiple types of transcription factors performing their functions simultaneously inside the cell, I will explore the extent of regulatory crosstalk -- incorrect binding interactions between transcription factors and binding sites that lead to erroneous regulatory states -- and understand the constraints this places on the design of regulatory systems. I will then develop a generic theoretical framework to investigate the coevolution of multiple transcription factors and multiple binding sites, in the context of a gene regulatory network that performs a certain function. As a particular tractable version of this problem, I will consider the evolution of two transcription factors when they transmit upstream signals to downstream target genes. Specifically, I will describe the evolutionary steady states and the evolutionary pathways involved, along with their timescales, of a system that initially undergoes a transcription factor duplication event. To connect this important theoretical model to the prominent biological event of transcription factor duplication giving rise to paralogous families, I will then describe a bioinformatics analysis of C2H2 Zn-finger transcription factors, a major family in humans, and focus on the patterns of evolution that paralogs have undergone in their various protein domains in the recent past. ' alternative_title: - ISTA Thesis article_processing_charge: No author: - first_name: Roshan full_name: Prizak, Roshan id: 4456104E-F248-11E8-B48F-1D18A9856A87 last_name: Prizak citation: ama: Prizak R. Coevolution of transcription factors and their binding sites in sequence space. 2019. doi:10.15479/at:ista:th6071 apa: Prizak, R. (2019). Coevolution of transcription factors and their binding sites in sequence space. Institute of Science and Technology Austria. https://doi.org/10.15479/at:ista:th6071 chicago: Prizak, Roshan. “Coevolution of Transcription Factors and Their Binding Sites in Sequence Space.” Institute of Science and Technology Austria, 2019. https://doi.org/10.15479/at:ista:th6071. ieee: R. Prizak, “Coevolution of transcription factors and their binding sites in sequence space,” Institute of Science and Technology Austria, 2019. ista: Prizak R. 2019. Coevolution of transcription factors and their binding sites in sequence space. Institute of Science and Technology Austria. mla: Prizak, Roshan. Coevolution of Transcription Factors and Their Binding Sites in Sequence Space. Institute of Science and Technology Austria, 2019, doi:10.15479/at:ista:th6071. short: R. Prizak, Coevolution of Transcription Factors and Their Binding Sites in Sequence Space, Institute of Science and Technology Austria, 2019. date_created: 2019-03-06T16:16:10Z date_published: 2019-03-11T00:00:00Z date_updated: 2023-09-22T10:00:48Z day: '11' ddc: - '576' degree_awarded: PhD department: - _id: GaTk - _id: NiBa doi: 10.15479/at:ista:th6071 file: - access_level: open_access checksum: e60a72de35d270b31f1a23d50f224ec0 content_type: application/pdf creator: rprizak date_created: 2019-03-06T16:05:07Z date_updated: 2020-07-14T12:47:18Z file_id: '6072' file_name: Thesis_final_PDFA_RoshanPrizak.pdf file_size: 20995465 relation: main_file - access_level: closed checksum: 67c2630333d05ebafef5f018863a8465 content_type: application/zip creator: rprizak date_created: 2019-03-06T16:09:39Z date_updated: 2020-07-14T12:47:18Z file_id: '6073' file_name: thesis_v2_merge.zip file_size: 85705272 relation: source_file title: Latex files file_date_updated: 2020-07-14T12:47:18Z has_accepted_license: '1' language: - iso: eng month: '03' oa: 1 oa_version: Published Version page: '189' project: - _id: 254E9036-B435-11E9-9278-68D0E5697425 call_identifier: FWF grant_number: P28844-B27 name: Biophysics of information processing in gene regulation publication_identifier: issn: - 2663-337X publication_status: published publisher: Institute of Science and Technology Austria related_material: record: - id: '1358' relation: part_of_dissertation status: public - id: '955' relation: part_of_dissertation status: public status: public supervisor: - first_name: Gašper full_name: Tkačik, Gašper id: 3D494DCA-F248-11E8-B48F-1D18A9856A87 last_name: Tkačik orcid: 0000-0002-6699-1455 title: Coevolution of transcription factors and their binding sites in sequence space type: dissertation user_id: c635000d-4b10-11ee-a964-aac5a93f6ac1 year: '2019' ... --- _id: '7103' abstract: - lang: eng text: Origin and functions of intermittent transitions among sleep stages, including short awakenings and arousals, constitute a challenge to the current homeostatic framework for sleep regulation, focusing on factors modulating sleep over large time scales. Here we propose that the complex micro-architecture characterizing the sleep-wake cycle results from an underlying non-equilibrium critical dynamics, bridging collective behaviors across spatio-temporal scales. We investigate θ and δ wave dynamics in control rats and in rats with lesions of sleep-promoting neurons in the parafacial zone. We demonstrate that intermittent bursts in θ and δ rhythms exhibit a complex temporal organization, with long-range power-law correlations and a robust duality of power law (θ-bursts, active phase) and exponential-like (δ-bursts, quiescent phase) duration distributions, typical features of non-equilibrium systems self-organizing at criticality. Crucially, such temporal organization relates to anti-correlated coupling between θ- and δ-bursts, and is independent of the dominant physiologic state and lesions, a solid indication of a basic principle in sleep dynamics. article_number: e1007268 article_processing_charge: No article_type: original author: - first_name: Jilin W. J. L. full_name: Wang, Jilin W. J. L. last_name: Wang - first_name: Fabrizio full_name: Lombardi, Fabrizio id: A057D288-3E88-11E9-986D-0CF4E5697425 last_name: Lombardi orcid: 0000-0003-2623-5249 - first_name: Xiyun full_name: Zhang, Xiyun last_name: Zhang - first_name: Christelle full_name: Anaclet, Christelle last_name: Anaclet - first_name: Plamen Ch. full_name: Ivanov, Plamen Ch. last_name: Ivanov citation: ama: Wang JWJL, Lombardi F, Zhang X, Anaclet C, Ivanov PC. Non-equilibrium critical dynamics of bursts in θ and δ rhythms as fundamental characteristic of sleep and wake micro-architecture. PLoS Computational Biology. 2019;15(11). doi:10.1371/journal.pcbi.1007268 apa: Wang, J. W. J. L., Lombardi, F., Zhang, X., Anaclet, C., & Ivanov, P. C. (2019). Non-equilibrium critical dynamics of bursts in θ and δ rhythms as fundamental characteristic of sleep and wake micro-architecture. PLoS Computational Biology. Public Library of Science. https://doi.org/10.1371/journal.pcbi.1007268 chicago: Wang, Jilin W. J. L., Fabrizio Lombardi, Xiyun Zhang, Christelle Anaclet, and Plamen Ch. Ivanov. “Non-Equilibrium Critical Dynamics of Bursts in θ and δ Rhythms as Fundamental Characteristic of Sleep and Wake Micro-Architecture.” PLoS Computational Biology. Public Library of Science, 2019. https://doi.org/10.1371/journal.pcbi.1007268. ieee: J. W. J. L. Wang, F. Lombardi, X. Zhang, C. Anaclet, and P. C. Ivanov, “Non-equilibrium critical dynamics of bursts in θ and δ rhythms as fundamental characteristic of sleep and wake micro-architecture,” PLoS Computational Biology, vol. 15, no. 11. Public Library of Science, 2019. ista: Wang JWJL, Lombardi F, Zhang X, Anaclet C, Ivanov PC. 2019. Non-equilibrium critical dynamics of bursts in θ and δ rhythms as fundamental characteristic of sleep and wake micro-architecture. PLoS Computational Biology. 15(11), e1007268. mla: Wang, Jilin W. J. L., et al. “Non-Equilibrium Critical Dynamics of Bursts in θ and δ Rhythms as Fundamental Characteristic of Sleep and Wake Micro-Architecture.” PLoS Computational Biology, vol. 15, no. 11, e1007268, Public Library of Science, 2019, doi:10.1371/journal.pcbi.1007268. short: J.W.J.L. Wang, F. Lombardi, X. Zhang, C. Anaclet, P.C. Ivanov, PLoS Computational Biology 15 (2019). date_created: 2019-11-25T08:20:47Z date_published: 2019-11-01T00:00:00Z date_updated: 2023-10-17T12:30:07Z day: '01' ddc: - '570' - '000' department: - _id: GaTk doi: 10.1371/journal.pcbi.1007268 ec_funded: 1 external_id: isi: - '000500976100014' pmid: - '31725712' file: - access_level: open_access checksum: 2a096a9c6dcc6eaa94077b2603bc6c12 content_type: application/pdf creator: dernst date_created: 2019-11-25T08:24:01Z date_updated: 2020-07-14T12:47:49Z file_id: '7104' file_name: 2019_PLOSComBio_Wang.pdf file_size: 3982516 relation: main_file file_date_updated: 2020-07-14T12:47:49Z has_accepted_license: '1' intvolume: ' 15' isi: 1 issue: '11' language: - iso: eng month: '11' oa: 1 oa_version: Published Version pmid: 1 project: - _id: 260C2330-B435-11E9-9278-68D0E5697425 call_identifier: H2020 grant_number: '754411' name: ISTplus - Postdoctoral Fellowships publication: PLoS Computational Biology publication_identifier: issn: - 1553-7358 publication_status: published publisher: Public Library of Science quality_controlled: '1' scopus_import: '1' status: public title: Non-equilibrium critical dynamics of bursts in θ and δ rhythms as fundamental characteristic of sleep and wake micro-architecture tmp: image: /images/cc_by.png legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0) short: CC BY (4.0) type: journal_article user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87 volume: 15 year: '2019' ... --- _id: '6090' abstract: - lang: eng text: Cells need to reliably sense external ligand concentrations to achieve various biological functions such as chemotaxis or signaling. The molecular recognition of ligands by surface receptors is degenerate in many systems, leading to crosstalk between ligand-receptor pairs. Crosstalk is often thought of as a deviation from optimal specific recognition, as the binding of noncognate ligands can interfere with the detection of the receptor's cognate ligand, possibly leading to a false triggering of a downstream signaling pathway. Here we quantify the optimal precision of sensing the concentrations of multiple ligands by a collection of promiscuous receptors. We demonstrate that crosstalk can improve precision in concentration sensing and discrimination tasks. To achieve superior precision, the additional information about ligand concentrations contained in short binding events of the noncognate ligand should be exploited. We present a proofreading scheme to realize an approximate estimation of multiple ligand concentrations that reaches a precision close to the derived optimal bounds. Our results help rationalize the observed ubiquity of receptor crosstalk in molecular sensing. article_number: '022423' article_processing_charge: No author: - first_name: Martín full_name: Carballo-Pacheco, Martín last_name: Carballo-Pacheco - first_name: Jonathan full_name: Desponds, Jonathan last_name: Desponds - first_name: Tatyana full_name: Gavrilchenko, Tatyana last_name: Gavrilchenko - first_name: Andreas full_name: Mayer, Andreas last_name: Mayer - first_name: Roshan full_name: Prizak, Roshan id: 4456104E-F248-11E8-B48F-1D18A9856A87 last_name: Prizak - first_name: Gautam full_name: Reddy, Gautam last_name: Reddy - first_name: Ilya full_name: Nemenman, Ilya last_name: Nemenman - first_name: Thierry full_name: Mora, Thierry last_name: Mora citation: ama: Carballo-Pacheco M, Desponds J, Gavrilchenko T, et al. Receptor crosstalk improves concentration sensing of multiple ligands. Physical Review E. 2019;99(2). doi:10.1103/PhysRevE.99.022423 apa: Carballo-Pacheco, M., Desponds, J., Gavrilchenko, T., Mayer, A., Prizak, R., Reddy, G., … Mora, T. (2019). Receptor crosstalk improves concentration sensing of multiple ligands. Physical Review E. American Physical Society. https://doi.org/10.1103/PhysRevE.99.022423 chicago: Carballo-Pacheco, Martín, Jonathan Desponds, Tatyana Gavrilchenko, Andreas Mayer, Roshan Prizak, Gautam Reddy, Ilya Nemenman, and Thierry Mora. “Receptor Crosstalk Improves Concentration Sensing of Multiple Ligands.” Physical Review E. American Physical Society, 2019. https://doi.org/10.1103/PhysRevE.99.022423. ieee: M. Carballo-Pacheco et al., “Receptor crosstalk improves concentration sensing of multiple ligands,” Physical Review E, vol. 99, no. 2. American Physical Society, 2019. ista: Carballo-Pacheco M, Desponds J, Gavrilchenko T, Mayer A, Prizak R, Reddy G, Nemenman I, Mora T. 2019. Receptor crosstalk improves concentration sensing of multiple ligands. Physical Review E. 99(2), 022423. mla: Carballo-Pacheco, Martín, et al. “Receptor Crosstalk Improves Concentration Sensing of Multiple Ligands.” Physical Review E, vol. 99, no. 2, 022423, American Physical Society, 2019, doi:10.1103/PhysRevE.99.022423. short: M. Carballo-Pacheco, J. Desponds, T. Gavrilchenko, A. Mayer, R. Prizak, G. Reddy, I. Nemenman, T. Mora, Physical Review E 99 (2019). date_created: 2019-03-10T22:59:20Z date_published: 2019-02-26T00:00:00Z date_updated: 2024-02-28T13:12:06Z day: '26' department: - _id: NiBa - _id: GaTk doi: 10.1103/PhysRevE.99.022423 external_id: isi: - '000459916500007' intvolume: ' 99' isi: 1 issue: '2' language: - iso: eng main_file_link: - open_access: '1' url: https://www.biorxiv.org/content/10.1101/448118v1.abstract month: '02' oa: 1 oa_version: Preprint publication: Physical Review E publication_status: published publisher: American Physical Society quality_controlled: '1' scopus_import: '1' status: public title: Receptor crosstalk improves concentration sensing of multiple ligands type: journal_article user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87 volume: 99 year: '2019' ... --- _id: '7606' abstract: - lang: eng text: We derive a tight lower bound on equivocation (conditional entropy), or equivalently a tight upper bound on mutual information between a signal variable and channel outputs. The bound is in terms of the joint distribution of the signals and maximum a posteriori decodes (most probable signals given channel output). As part of our derivation, we describe the key properties of the distribution of signals, channel outputs and decodes, that minimizes equivocation and maximizes mutual information. This work addresses a problem in data analysis, where mutual information between signals and decodes is sometimes used to lower bound the mutual information between signals and channel outputs. Our result provides a corresponding upper bound. article_number: '8989292' article_processing_charge: No author: - first_name: Michal full_name: Hledik, Michal id: 4171253A-F248-11E8-B48F-1D18A9856A87 last_name: Hledik - first_name: Thomas R full_name: Sokolowski, Thomas R id: 3E999752-F248-11E8-B48F-1D18A9856A87 last_name: Sokolowski orcid: 0000-0002-1287-3779 - first_name: Gašper full_name: Tkačik, Gašper id: 3D494DCA-F248-11E8-B48F-1D18A9856A87 last_name: Tkačik orcid: 0000-0002-6699-1455 citation: ama: 'Hledik M, Sokolowski TR, Tkačik G. A tight upper bound on mutual information. In: IEEE Information Theory Workshop, ITW 2019. IEEE; 2019. doi:10.1109/ITW44776.2019.8989292' apa: 'Hledik, M., Sokolowski, T. R., & Tkačik, G. (2019). A tight upper bound on mutual information. In IEEE Information Theory Workshop, ITW 2019. Visby, Sweden: IEEE. https://doi.org/10.1109/ITW44776.2019.8989292' chicago: Hledik, Michal, Thomas R Sokolowski, and Gašper Tkačik. “A Tight Upper Bound on Mutual Information.” In IEEE Information Theory Workshop, ITW 2019. IEEE, 2019. https://doi.org/10.1109/ITW44776.2019.8989292. ieee: M. Hledik, T. R. Sokolowski, and G. Tkačik, “A tight upper bound on mutual information,” in IEEE Information Theory Workshop, ITW 2019, Visby, Sweden, 2019. ista: Hledik M, Sokolowski TR, Tkačik G. 2019. A tight upper bound on mutual information. IEEE Information Theory Workshop, ITW 2019. Information Theory Workshop, 8989292. mla: Hledik, Michal, et al. “A Tight Upper Bound on Mutual Information.” IEEE Information Theory Workshop, ITW 2019, 8989292, IEEE, 2019, doi:10.1109/ITW44776.2019.8989292. short: M. Hledik, T.R. Sokolowski, G. Tkačik, in:, IEEE Information Theory Workshop, ITW 2019, IEEE, 2019. conference: end_date: 2019-08-28 location: Visby, Sweden name: Information Theory Workshop start_date: 2019-08-25 date_created: 2020-03-22T23:00:47Z date_published: 2019-08-01T00:00:00Z date_updated: 2024-03-06T14:22:51Z day: '01' department: - _id: GaTk doi: 10.1109/ITW44776.2019.8989292 ec_funded: 1 external_id: arxiv: - '1812.01475' isi: - '000540384500015' isi: 1 language: - iso: eng main_file_link: - open_access: '1' url: https://arxiv.org/abs/1812.01475 month: '08' oa: 1 oa_version: Preprint project: - _id: 2564DBCA-B435-11E9-9278-68D0E5697425 call_identifier: H2020 grant_number: '665385' name: International IST Doctoral Program publication: IEEE Information Theory Workshop, ITW 2019 publication_identifier: isbn: - '9781538669006' publication_status: published publisher: IEEE quality_controlled: '1' related_material: record: - id: '15020' relation: dissertation_contains status: public scopus_import: '1' status: public title: A tight upper bound on mutual information type: conference user_id: c635000d-4b10-11ee-a964-aac5a93f6ac1 year: '2019' ... --- _id: '306' abstract: - lang: eng text: A cornerstone of statistical inference, the maximum entropy framework is being increasingly applied to construct descriptive and predictive models of biological systems, especially complex biological networks, from large experimental data sets. Both its broad applicability and the success it obtained in different contexts hinge upon its conceptual simplicity and mathematical soundness. Here we try to concisely review the basic elements of the maximum entropy principle, starting from the notion of ‘entropy’, and describe its usefulness for the analysis of biological systems. As examples, we focus specifically on the problem of reconstructing gene interaction networks from expression data and on recent work attempting to expand our system-level understanding of bacterial metabolism. Finally, we highlight some extensions and potential limitations of the maximum entropy approach, and point to more recent developments that are likely to play a key role in the upcoming challenges of extracting structures and information from increasingly rich, high-throughput biological data. article_number: e00596 author: - first_name: Andrea full_name: De Martino, Andrea last_name: De Martino - first_name: Daniele full_name: De Martino, Daniele id: 3FF5848A-F248-11E8-B48F-1D18A9856A87 last_name: De Martino orcid: 0000-0002-5214-4706 citation: ama: De Martino A, De Martino D. An introduction to the maximum entropy approach and its application to inference problems in biology. Heliyon. 2018;4(4). doi:10.1016/j.heliyon.2018.e00596 apa: De Martino, A., & De Martino, D. (2018). An introduction to the maximum entropy approach and its application to inference problems in biology. Heliyon. Elsevier. https://doi.org/10.1016/j.heliyon.2018.e00596 chicago: De Martino, Andrea, and Daniele De Martino. “An Introduction to the Maximum Entropy Approach and Its Application to Inference Problems in Biology.” Heliyon. Elsevier, 2018. https://doi.org/10.1016/j.heliyon.2018.e00596. ieee: A. De Martino and D. De Martino, “An introduction to the maximum entropy approach and its application to inference problems in biology,” Heliyon, vol. 4, no. 4. Elsevier, 2018. ista: De Martino A, De Martino D. 2018. An introduction to the maximum entropy approach and its application to inference problems in biology. Heliyon. 4(4), e00596. mla: De Martino, Andrea, and Daniele De Martino. “An Introduction to the Maximum Entropy Approach and Its Application to Inference Problems in Biology.” Heliyon, vol. 4, no. 4, e00596, Elsevier, 2018, doi:10.1016/j.heliyon.2018.e00596. short: A. De Martino, D. De Martino, Heliyon 4 (2018). date_created: 2018-12-11T11:45:44Z date_published: 2018-04-01T00:00:00Z date_updated: 2021-01-12T07:40:46Z day: '01' ddc: - '530' department: - _id: GaTk doi: 10.1016/j.heliyon.2018.e00596 ec_funded: 1 file: - access_level: open_access checksum: 67010cf5e3b3e0637c659371714a715a content_type: application/pdf creator: dernst date_created: 2019-02-06T07:36:24Z date_updated: 2020-07-14T12:45:59Z file_id: '5929' file_name: 2018_Heliyon_DeMartino.pdf file_size: 994490 relation: main_file file_date_updated: 2020-07-14T12:45:59Z has_accepted_license: '1' intvolume: ' 4' issue: '4' language: - iso: eng month: '04' oa: 1 oa_version: Published Version project: - _id: 25681D80-B435-11E9-9278-68D0E5697425 call_identifier: FP7 grant_number: '291734' name: International IST Postdoc Fellowship Programme publication: Heliyon publication_status: published publisher: Elsevier quality_controlled: '1' scopus_import: 1 status: public title: An introduction to the maximum entropy approach and its application to inference problems in biology tmp: image: /images/cc_by.png legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0) short: CC BY (4.0) type: journal_article user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87 volume: 4 year: '2018' ... --- _id: '305' abstract: - lang: eng text: The hanging-drop network (HDN) is a technology platform based on a completely open microfluidic network at the bottom of an inverted, surface-patterned substrate. The platform is predominantly used for the formation, culturing, and interaction of self-assembled spherical microtissues (spheroids) under precisely controlled flow conditions. Here, we describe design, fabrication, and operation of microfluidic hanging-drop networks. acknowledgement: This work was financially supported by FP7 of the EU through the project “Body on a chip,” ICT-FET-296257, and the ERC Advanced Grant “NeuroCMOS” (contract 267351), as well as by an individual Ambizione Grant 142440 from the Swiss National Science Foundation for Olivier Frey. The research leading to these results also received funding from the People Programme (Marie Curie Actions) of the European Union’s Seventh Framework Programme (FP7/2007-2013) under REA grant agreement no. [291734]. We would like to thank Alexander Stettler, ETH Zurich for his expertise and support in the cleanroom, and we acknowledge the Single Cell Unit of D-BSSE, ETH Zurich for assistance in microscopy issues. M.L. is grateful to the members of the Guet and Tkačik groups, IST Austria, for valuable comments and support. alternative_title: - MIMB author: - first_name: Patrick full_name: Misun, Patrick last_name: Misun - first_name: Axel full_name: Birchler, Axel last_name: Birchler - first_name: Moritz full_name: Lang, Moritz id: 29E0800A-F248-11E8-B48F-1D18A9856A87 last_name: Lang - first_name: Andreas full_name: Hierlemann, Andreas last_name: Hierlemann - first_name: Olivier full_name: Frey, Olivier last_name: Frey citation: ama: Misun P, Birchler A, Lang M, Hierlemann A, Frey O. Fabrication and operation of microfluidic hanging drop networks. Methods in Molecular Biology. 2018;1771:183-202. doi:10.1007/978-1-4939-7792-5_15 apa: Misun, P., Birchler, A., Lang, M., Hierlemann, A., & Frey, O. (2018). Fabrication and operation of microfluidic hanging drop networks. Methods in Molecular Biology. Springer. https://doi.org/10.1007/978-1-4939-7792-5_15 chicago: Misun, Patrick, Axel Birchler, Moritz Lang, Andreas Hierlemann, and Olivier Frey. “Fabrication and Operation of Microfluidic Hanging Drop Networks.” Methods in Molecular Biology. Springer, 2018. https://doi.org/10.1007/978-1-4939-7792-5_15. ieee: P. Misun, A. Birchler, M. Lang, A. Hierlemann, and O. Frey, “Fabrication and operation of microfluidic hanging drop networks,” Methods in Molecular Biology, vol. 1771. Springer, pp. 183–202, 2018. ista: Misun P, Birchler A, Lang M, Hierlemann A, Frey O. 2018. Fabrication and operation of microfluidic hanging drop networks. Methods in Molecular Biology. 1771, 183–202. mla: Misun, Patrick, et al. “Fabrication and Operation of Microfluidic Hanging Drop Networks.” Methods in Molecular Biology, vol. 1771, Springer, 2018, pp. 183–202, doi:10.1007/978-1-4939-7792-5_15. short: P. Misun, A. Birchler, M. Lang, A. Hierlemann, O. Frey, Methods in Molecular Biology 1771 (2018) 183–202. date_created: 2018-12-11T11:45:43Z date_published: 2018-01-01T00:00:00Z date_updated: 2021-01-12T07:40:42Z day: '01' department: - _id: CaGu - _id: GaTk doi: 10.1007/978-1-4939-7792-5_15 ec_funded: 1 intvolume: ' 1771' language: - iso: eng month: '01' oa_version: None page: 183 - 202 project: - _id: 25681D80-B435-11E9-9278-68D0E5697425 call_identifier: FP7 grant_number: '291734' name: International IST Postdoc Fellowship Programme publication: Methods in Molecular Biology publication_status: published publisher: Springer publist_id: '7574' quality_controlled: '1' scopus_import: 1 status: public title: Fabrication and operation of microfluidic hanging drop networks type: journal_article user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87 volume: 1771 year: '2018' ... --- _id: '281' abstract: - lang: eng text: 'Although cells respond specifically to environments, how environmental identity is encoded intracellularly is not understood. Here, we study this organization of information in budding yeast by estimating the mutual information between environmental transitions and the dynamics of nuclear translocation for 10 transcription factors. Our method of estimation is general, scalable, and based on decoding from single cells. The dynamics of the transcription factors are necessary to encode the highest amounts of extracellular information, and we show that information is transduced through two channels: Generalists (Msn2/4, Tod6 and Dot6, Maf1, and Sfp1) can encode the nature of multiple stresses, but only if stress is high; specialists (Hog1, Yap1, and Mig1/2) encode one particular stress, but do so more quickly and for a wider range of magnitudes. In particular, Dot6 encodes almost as much information as Msn2, the master regulator of the environmental stress response. Each transcription factor reports differently, and it is only their collective behavior that distinguishes between multiple environmental states. Changes in the dynamics of the localization of transcription factors thus constitute a precise, distributed internal representation of extracellular change. We predict that such multidimensional representations are common in cellular decision-making.' acknowledgement: This work was supported by the Biotechnology and Biological Sciences Research Council (J.M.J.P., I.F., and P.S.S.), the Engineering and Physical Sciences Research Council (EPSRC) (A.A.G.), and Austrian Science Fund Grant FWF P28844 (to G.T.). article_processing_charge: No article_type: original author: - first_name: Alejandro full_name: Granados, Alejandro last_name: Granados - first_name: Julian full_name: Pietsch, Julian last_name: Pietsch - first_name: Sarah A full_name: Cepeda Humerez, Sarah A id: 3DEE19A4-F248-11E8-B48F-1D18A9856A87 last_name: Cepeda Humerez - first_name: Isebail full_name: Farquhar, Isebail last_name: Farquhar - first_name: Gasper full_name: Tkacik, Gasper id: 3D494DCA-F248-11E8-B48F-1D18A9856A87 last_name: Tkacik orcid: 0000-0002-6699-1455 - first_name: Peter full_name: Swain, Peter last_name: Swain citation: ama: Granados A, Pietsch J, Cepeda Humerez SA, Farquhar I, Tkačik G, Swain P. Distributed and dynamic intracellular organization of extracellular information. PNAS. 2018;115(23):6088-6093. doi:10.1073/pnas.1716659115 apa: Granados, A., Pietsch, J., Cepeda Humerez, S. A., Farquhar, I., Tkačik, G., & Swain, P. (2018). Distributed and dynamic intracellular organization of extracellular information. PNAS. National Academy of Sciences. https://doi.org/10.1073/pnas.1716659115 chicago: Granados, Alejandro, Julian Pietsch, Sarah A Cepeda Humerez, Isebail Farquhar, Gašper Tkačik, and Peter Swain. “Distributed and Dynamic Intracellular Organization of Extracellular Information.” PNAS. National Academy of Sciences, 2018. https://doi.org/10.1073/pnas.1716659115. ieee: A. Granados, J. Pietsch, S. A. Cepeda Humerez, I. Farquhar, G. Tkačik, and P. Swain, “Distributed and dynamic intracellular organization of extracellular information,” PNAS, vol. 115, no. 23. National Academy of Sciences, pp. 6088–6093, 2018. ista: Granados A, Pietsch J, Cepeda Humerez SA, Farquhar I, Tkačik G, Swain P. 2018. Distributed and dynamic intracellular organization of extracellular information. PNAS. 115(23), 6088–6093. mla: Granados, Alejandro, et al. “Distributed and Dynamic Intracellular Organization of Extracellular Information.” PNAS, vol. 115, no. 23, National Academy of Sciences, 2018, pp. 6088–93, doi:10.1073/pnas.1716659115. short: A. Granados, J. Pietsch, S.A. Cepeda Humerez, I. Farquhar, G. Tkačik, P. Swain, PNAS 115 (2018) 6088–6093. date_created: 2018-12-11T11:45:35Z date_published: 2018-06-05T00:00:00Z date_updated: 2023-09-11T12:58:24Z day: '05' department: - _id: GaTk doi: 10.1073/pnas.1716659115 external_id: isi: - '000434114900071' pmid: - '29784812' intvolume: ' 115' isi: 1 issue: '23' language: - iso: eng main_file_link: - open_access: '1' url: https://www.biorxiv.org/content/early/2017/09/21/192039 month: '06' oa: 1 oa_version: Preprint page: 6088 - 6093 pmid: 1 project: - _id: 254E9036-B435-11E9-9278-68D0E5697425 call_identifier: FWF grant_number: P28844-B27 name: Biophysics of information processing in gene regulation publication: PNAS publication_status: published publisher: National Academy of Sciences publist_id: '7618' quality_controlled: '1' related_material: record: - id: '6473' relation: part_of_dissertation status: public scopus_import: '1' status: public title: Distributed and dynamic intracellular organization of extracellular information type: journal_article user_id: c635000d-4b10-11ee-a964-aac5a93f6ac1 volume: 115 year: '2018' ... --- _id: '316' abstract: - lang: eng text: 'Self-incompatibility (SI) is a genetically based recognition system that functions to prevent self-fertilization and mating among related plants. An enduring puzzle in SI is how the high diversity observed in nature arises and is maintained. Based on the underlying recognition mechanism, SI can be classified into two main groups: self- and non-self recognition. Most work has focused on diversification within self-recognition systems despite expected differences between the two groups in the evolutionary pathways and outcomes of diversification. Here, we use a deterministic population genetic model and stochastic simulations to investigate how novel S-haplotypes evolve in a gametophytic non-self recognition (SRNase/S Locus F-box (SLF)) SI system. For this model the pathways for diversification involve either the maintenance or breakdown of SI and can vary in the order of mutations of the female (SRNase) and male (SLF) components. We show analytically that diversification can occur with high inbreeding depression and self-pollination, but this varies with evolutionary pathway and level of completeness (which determines the number of potential mating partners in the population), and in general is more likely for lower haplotype number. The conditions for diversification are broader in stochastic simulations of finite population size. However, the number of haplotypes observed under high inbreeding and moderate to high self-pollination is less than that commonly observed in nature. Diversification was observed through pathways that maintain SI as well as through self-compatible intermediates. Yet the lifespan of diversified haplotypes was sensitive to their level of completeness. By examining diversification in a non-self recognition SI system, this model extends our understanding of the evolution and maintenance of haplotype diversity observed in a self recognition system common in flowering plants.' article_processing_charge: No article_type: original author: - first_name: Katarina full_name: Bodova, Katarina id: 2BA24EA0-F248-11E8-B48F-1D18A9856A87 last_name: Bodova orcid: 0000-0002-7214-0171 - first_name: Tadeas full_name: Priklopil, Tadeas id: 3C869AA0-F248-11E8-B48F-1D18A9856A87 last_name: Priklopil - first_name: David full_name: Field, David id: 419049E2-F248-11E8-B48F-1D18A9856A87 last_name: Field orcid: 0000-0002-4014-8478 - first_name: Nicholas H full_name: Barton, Nicholas H id: 4880FE40-F248-11E8-B48F-1D18A9856A87 last_name: Barton orcid: 0000-0002-8548-5240 - first_name: Melinda full_name: Pickup, Melinda id: 2C78037E-F248-11E8-B48F-1D18A9856A87 last_name: Pickup orcid: 0000-0001-6118-0541 citation: ama: Bodova K, Priklopil T, Field D, Barton NH, Pickup M. Evolutionary pathways for the generation of new self-incompatibility haplotypes in a non-self recognition system. Genetics. 2018;209(3):861-883. doi:10.1534/genetics.118.300748 apa: Bodova, K., Priklopil, T., Field, D., Barton, N. H., & Pickup, M. (2018). Evolutionary pathways for the generation of new self-incompatibility haplotypes in a non-self recognition system. Genetics. Genetics Society of America. https://doi.org/10.1534/genetics.118.300748 chicago: Bodova, Katarina, Tadeas Priklopil, David Field, Nicholas H Barton, and Melinda Pickup. “Evolutionary Pathways for the Generation of New Self-Incompatibility Haplotypes in a Non-Self Recognition System.” Genetics. Genetics Society of America, 2018. https://doi.org/10.1534/genetics.118.300748. ieee: K. Bodova, T. Priklopil, D. Field, N. H. Barton, and M. Pickup, “Evolutionary pathways for the generation of new self-incompatibility haplotypes in a non-self recognition system,” Genetics, vol. 209, no. 3. Genetics Society of America, pp. 861–883, 2018. ista: Bodova K, Priklopil T, Field D, Barton NH, Pickup M. 2018. Evolutionary pathways for the generation of new self-incompatibility haplotypes in a non-self recognition system. Genetics. 209(3), 861–883. mla: Bodova, Katarina, et al. “Evolutionary Pathways for the Generation of New Self-Incompatibility Haplotypes in a Non-Self Recognition System.” Genetics, vol. 209, no. 3, Genetics Society of America, 2018, pp. 861–83, doi:10.1534/genetics.118.300748. short: K. Bodova, T. Priklopil, D. Field, N.H. Barton, M. Pickup, Genetics 209 (2018) 861–883. date_created: 2018-12-11T11:45:47Z date_published: 2018-07-01T00:00:00Z date_updated: 2023-09-11T13:57:43Z day: '01' department: - _id: NiBa - _id: GaTk doi: 10.1534/genetics.118.300748 ec_funded: 1 external_id: isi: - '000437171700017' intvolume: ' 209' isi: 1 issue: '3' language: - iso: eng main_file_link: - open_access: '1' url: https://www.biorxiv.org/node/80098.abstract month: '07' oa: 1 oa_version: Preprint page: 861-883 project: - _id: 25B36484-B435-11E9-9278-68D0E5697425 call_identifier: FP7 grant_number: '329960' name: Mating system and the evolutionary dynamics of hybrid zones - _id: 25B07788-B435-11E9-9278-68D0E5697425 call_identifier: FP7 grant_number: '250152' name: Limits to selection in biology and in evolutionary computation - _id: 25681D80-B435-11E9-9278-68D0E5697425 call_identifier: FP7 grant_number: '291734' name: International IST Postdoc Fellowship Programme publication: Genetics publication_status: published publisher: Genetics Society of America quality_controlled: '1' related_material: link: - description: News on IST Homepage relation: press_release url: https://ist.ac.at/en/news/recognizing-others-but-not-yourself-new-insights-into-the-evolution-of-plant-mating/ record: - id: '9813' relation: research_data status: public scopus_import: '1' status: public title: Evolutionary pathways for the generation of new self-incompatibility haplotypes in a non-self recognition system type: journal_article user_id: c635000d-4b10-11ee-a964-aac5a93f6ac1 volume: 209 year: '2018' ... --- _id: '9813' abstract: - lang: eng text: 'File S1 contains figures that clarify the following features: (i) effect of population size on the average number/frequency of SI classes, (ii) changes in the minimal completeness deficit in time for a single class, and (iii) diversification diagrams for all studied pathways, including the summary figure for k = 8. File S2 contains the code required for a stochastic simulation of the SLF system with an example. This file also includes the output in the form of figures and tables.' article_processing_charge: No author: - first_name: Katarína full_name: Bod'ová, Katarína id: 2BA24EA0-F248-11E8-B48F-1D18A9856A87 last_name: Bod'ová orcid: 0000-0002-7214-0171 - first_name: Tadeas full_name: Priklopil, Tadeas id: 3C869AA0-F248-11E8-B48F-1D18A9856A87 last_name: Priklopil - first_name: David full_name: Field, David id: 419049E2-F248-11E8-B48F-1D18A9856A87 last_name: Field orcid: 0000-0002-4014-8478 - first_name: Nicholas H full_name: Barton, Nicholas H id: 4880FE40-F248-11E8-B48F-1D18A9856A87 last_name: Barton orcid: 0000-0002-8548-5240 - first_name: Melinda full_name: Pickup, Melinda id: 2C78037E-F248-11E8-B48F-1D18A9856A87 last_name: Pickup orcid: 0000-0001-6118-0541 citation: ama: Bodova K, Priklopil T, Field D, Barton NH, Pickup M. Supplemental material for Bodova et al., 2018. 2018. doi:10.25386/genetics.6148304.v1 apa: Bodova, K., Priklopil, T., Field, D., Barton, N. H., & Pickup, M. (2018). Supplemental material for Bodova et al., 2018. Genetics Society of America. https://doi.org/10.25386/genetics.6148304.v1 chicago: Bodova, Katarina, Tadeas Priklopil, David Field, Nicholas H Barton, and Melinda Pickup. “Supplemental Material for Bodova et Al., 2018.” Genetics Society of America, 2018. https://doi.org/10.25386/genetics.6148304.v1. ieee: K. Bodova, T. Priklopil, D. Field, N. H. Barton, and M. Pickup, “Supplemental material for Bodova et al., 2018.” Genetics Society of America, 2018. ista: Bodova K, Priklopil T, Field D, Barton NH, Pickup M. 2018. Supplemental material for Bodova et al., 2018, Genetics Society of America, 10.25386/genetics.6148304.v1. mla: Bodova, Katarina, et al. Supplemental Material for Bodova et Al., 2018. Genetics Society of America, 2018, doi:10.25386/genetics.6148304.v1. short: K. Bodova, T. Priklopil, D. Field, N.H. Barton, M. Pickup, (2018). date_created: 2021-08-06T13:04:32Z date_published: 2018-04-30T00:00:00Z date_updated: 2023-09-11T13:57:42Z day: '30' department: - _id: NiBa - _id: GaTk doi: 10.25386/genetics.6148304.v1 main_file_link: - open_access: '1' url: https://doi.org/10.25386/genetics.6148304.v1 month: '04' oa: 1 oa_version: Published Version publisher: Genetics Society of America related_material: record: - id: '316' relation: used_in_publication status: public status: public title: Supplemental material for Bodova et al., 2018 type: research_data_reference user_id: 6785fbc1-c503-11eb-8a32-93094b40e1cf year: '2018' ... --- _id: '406' abstract: - lang: eng text: 'Recent developments in automated tracking allow uninterrupted, high-resolution recording of animal trajectories, sometimes coupled with the identification of stereotyped changes of body pose or other behaviors of interest. Analysis and interpretation of such data represents a challenge: the timing of animal behaviors may be stochastic and modulated by kinematic variables, by the interaction with the environment or with the conspecifics within the animal group, and dependent on internal cognitive or behavioral state of the individual. Existing models for collective motion typically fail to incorporate the discrete, stochastic, and internal-state-dependent aspects of behavior, while models focusing on individual animal behavior typically ignore the spatial aspects of the problem. Here we propose a probabilistic modeling framework to address this gap. Each animal can switch stochastically between different behavioral states, with each state resulting in a possibly different law of motion through space. Switching rates for behavioral transitions can depend in a very general way, which we seek to identify from data, on the effects of the environment as well as the interaction between the animals. We represent the switching dynamics as a Generalized Linear Model and show that: (i) forward simulation of multiple interacting animals is possible using a variant of the Gillespie’s Stochastic Simulation Algorithm; (ii) formulated properly, the maximum likelihood inference of switching rate functions is tractably solvable by gradient descent; (iii) model selection can be used to identify factors that modulate behavioral state switching and to appropriately adjust model complexity to data. To illustrate our framework, we apply it to two synthetic models of animal motion and to real zebrafish tracking data. ' acknowledgement: This work was supported by the Human Frontier Science Program RGP0065/2012 (GT, ES). article_processing_charge: Yes author: - first_name: Katarína full_name: Bod’Ová, Katarína last_name: Bod’Ová - first_name: Gabriel full_name: Mitchell, Gabriel id: 315BCD80-F248-11E8-B48F-1D18A9856A87 last_name: Mitchell - first_name: Roy full_name: Harpaz, Roy last_name: Harpaz - first_name: Elad full_name: Schneidman, Elad last_name: Schneidman - first_name: Gasper full_name: Tkacik, Gasper id: 3D494DCA-F248-11E8-B48F-1D18A9856A87 last_name: Tkacik orcid: 0000-0002-6699-1455 citation: ama: Bod’Ová K, Mitchell G, Harpaz R, Schneidman E, Tkačik G. Probabilistic models of individual and collective animal behavior. PLoS One. 2018;13(3). doi:10.1371/journal.pone.0193049 apa: Bod’Ová, K., Mitchell, G., Harpaz, R., Schneidman, E., & Tkačik, G. (2018). Probabilistic models of individual and collective animal behavior. PLoS One. Public Library of Science. https://doi.org/10.1371/journal.pone.0193049 chicago: Bod’Ová, Katarína, Gabriel Mitchell, Roy Harpaz, Elad Schneidman, and Gašper Tkačik. “Probabilistic Models of Individual and Collective Animal Behavior.” PLoS One. Public Library of Science, 2018. https://doi.org/10.1371/journal.pone.0193049. ieee: K. Bod’Ová, G. Mitchell, R. Harpaz, E. Schneidman, and G. Tkačik, “Probabilistic models of individual and collective animal behavior,” PLoS One, vol. 13, no. 3. Public Library of Science, 2018. ista: Bod’Ová K, Mitchell G, Harpaz R, Schneidman E, Tkačik G. 2018. Probabilistic models of individual and collective animal behavior. PLoS One. 13(3). mla: Bod’Ová, Katarína, et al. “Probabilistic Models of Individual and Collective Animal Behavior.” PLoS One, vol. 13, no. 3, Public Library of Science, 2018, doi:10.1371/journal.pone.0193049. short: K. Bod’Ová, G. Mitchell, R. Harpaz, E. Schneidman, G. Tkačik, PLoS One 13 (2018). date_created: 2018-12-11T11:46:18Z date_published: 2018-03-07T00:00:00Z date_updated: 2023-09-15T12:06:19Z day: '07' ddc: - '530' - '571' department: - _id: GaTk doi: 10.1371/journal.pone.0193049 external_id: isi: - '000426896800032' file: - access_level: open_access checksum: 684229493db75b43e98a46cd922da497 content_type: application/pdf creator: system date_created: 2018-12-12T10:15:43Z date_updated: 2020-07-14T12:46:22Z file_id: '5165' file_name: IST-2018-995-v1+1_2018_Bodova_Probabilistic.pdf file_size: 6887358 relation: main_file file_date_updated: 2020-07-14T12:46:22Z has_accepted_license: '1' intvolume: ' 13' isi: 1 issue: '3' language: - iso: eng month: '03' oa: 1 oa_version: Submitted Version project: - _id: 255008E4-B435-11E9-9278-68D0E5697425 grant_number: RGP0065/2012 name: Information processing and computation in fish groups publication: PLoS One publication_status: published publisher: Public Library of Science publist_id: '7423' pubrep_id: '995' quality_controlled: '1' related_material: record: - id: '9831' relation: research_data status: public scopus_import: '1' status: public title: Probabilistic models of individual and collective animal behavior tmp: image: /images/cc_by.png legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0) short: CC BY (4.0) type: journal_article user_id: c635000d-4b10-11ee-a964-aac5a93f6ac1 volume: 13 year: '2018' ... --- _id: '457' abstract: - lang: eng text: Temperate bacteriophages integrate in bacterial genomes as prophages and represent an important source of genetic variation for bacterial evolution, frequently transmitting fitness-augmenting genes such as toxins responsible for virulence of major pathogens. However, only a fraction of bacteriophage infections are lysogenic and lead to prophage acquisition, whereas the majority are lytic and kill the infected bacteria. Unless able to discriminate lytic from lysogenic infections, mechanisms of immunity to bacteriophages are expected to act as a double-edged sword and increase the odds of survival at the cost of depriving bacteria of potentially beneficial prophages. We show that although restriction-modification systems as mechanisms of innate immunity prevent both lytic and lysogenic infections indiscriminately in individual bacteria, they increase the number of prophage-acquiring individuals at the population level. We find that this counterintuitive result is a consequence of phage-host population dynamics, in which restriction-modification systems delay infection onset until bacteria reach densities at which the probability of lysogeny increases. These results underscore the importance of population-level dynamics as a key factor modulating costs and benefits of immunity to temperate bacteriophages article_processing_charge: No author: - first_name: Maros full_name: Pleska, Maros id: 4569785E-F248-11E8-B48F-1D18A9856A87 last_name: Pleska orcid: 0000-0001-7460-7479 - first_name: Moritz full_name: Lang, Moritz id: 29E0800A-F248-11E8-B48F-1D18A9856A87 last_name: Lang - first_name: Dominik full_name: Refardt, Dominik last_name: Refardt - first_name: Bruce full_name: Levin, Bruce last_name: Levin - first_name: Calin C full_name: Guet, Calin C id: 47F8433E-F248-11E8-B48F-1D18A9856A87 last_name: Guet orcid: 0000-0001-6220-2052 citation: ama: Pleska M, Lang M, Refardt D, Levin B, Guet CC. Phage-host population dynamics promotes prophage acquisition in bacteria with innate immunity. Nature Ecology and Evolution. 2018;2(2):359-366. doi:10.1038/s41559-017-0424-z apa: Pleska, M., Lang, M., Refardt, D., Levin, B., & Guet, C. C. (2018). Phage-host population dynamics promotes prophage acquisition in bacteria with innate immunity. Nature Ecology and Evolution. Springer Nature. https://doi.org/10.1038/s41559-017-0424-z chicago: Pleska, Maros, Moritz Lang, Dominik Refardt, Bruce Levin, and Calin C Guet. “Phage-Host Population Dynamics Promotes Prophage Acquisition in Bacteria with Innate Immunity.” Nature Ecology and Evolution. Springer Nature, 2018. https://doi.org/10.1038/s41559-017-0424-z. ieee: M. Pleska, M. Lang, D. Refardt, B. Levin, and C. C. Guet, “Phage-host population dynamics promotes prophage acquisition in bacteria with innate immunity,” Nature Ecology and Evolution, vol. 2, no. 2. Springer Nature, pp. 359–366, 2018. ista: Pleska M, Lang M, Refardt D, Levin B, Guet CC. 2018. Phage-host population dynamics promotes prophage acquisition in bacteria with innate immunity. Nature Ecology and Evolution. 2(2), 359–366. mla: Pleska, Maros, et al. “Phage-Host Population Dynamics Promotes Prophage Acquisition in Bacteria with Innate Immunity.” Nature Ecology and Evolution, vol. 2, no. 2, Springer Nature, 2018, pp. 359–66, doi:10.1038/s41559-017-0424-z. short: M. Pleska, M. Lang, D. Refardt, B. Levin, C.C. Guet, Nature Ecology and Evolution 2 (2018) 359–366. date_created: 2018-12-11T11:46:35Z date_published: 2018-02-01T00:00:00Z date_updated: 2023-09-15T12:04:57Z day: '01' department: - _id: CaGu - _id: GaTk doi: 10.1038/s41559-017-0424-z ec_funded: 1 external_id: isi: - '000426516400027' intvolume: ' 2' isi: 1 issue: '2' language: - iso: eng month: '02' oa_version: None page: 359 - 366 project: - _id: 25681D80-B435-11E9-9278-68D0E5697425 call_identifier: FP7 grant_number: '291734' name: International IST Postdoc Fellowship Programme - _id: 251BCBEC-B435-11E9-9278-68D0E5697425 grant_number: RGY0079/2011 name: Multi-Level Conflicts in Evolutionary Dynamics of Restriction-Modification Systems (HFSP Young investigators' grant) - _id: 251D65D8-B435-11E9-9278-68D0E5697425 grant_number: '24210' name: Effects of Stochasticity on the Function of Restriction-Modi cation Systems at the Single-Cell Level (DOC Fellowship) publication: Nature Ecology and Evolution publication_status: published publisher: Springer Nature publist_id: '7364' quality_controlled: '1' related_material: record: - id: '202' relation: dissertation_contains status: public scopus_import: '1' status: public title: Phage-host population dynamics promotes prophage acquisition in bacteria with innate immunity type: journal_article user_id: c635000d-4b10-11ee-a964-aac5a93f6ac1 volume: 2 year: '2018' ... --- _id: '9831' abstract: - lang: eng text: 'Implementation of the inference method in Matlab, including three applications of the method: The first one for the model of ant motion, the second one for bacterial chemotaxis, and the third one for the motion of fish.' article_processing_charge: No author: - first_name: Katarína full_name: Bod’Ová, Katarína last_name: Bod’Ová - first_name: Gabriel full_name: Mitchell, Gabriel id: 315BCD80-F248-11E8-B48F-1D18A9856A87 last_name: Mitchell - first_name: Roy full_name: Harpaz, Roy last_name: Harpaz - first_name: Elad full_name: Schneidman, Elad last_name: Schneidman - first_name: Gašper full_name: Tkačik, Gašper id: 3D494DCA-F248-11E8-B48F-1D18A9856A87 last_name: Tkačik orcid: 0000-0002-6699-1455 citation: ama: Bod’Ová K, Mitchell G, Harpaz R, Schneidman E, Tkačik G. Implementation of the inference method in Matlab. 2018. doi:10.1371/journal.pone.0193049.s001 apa: Bod’Ová, K., Mitchell, G., Harpaz, R., Schneidman, E., & Tkačik, G. (2018). Implementation of the inference method in Matlab. Public Library of Science. https://doi.org/10.1371/journal.pone.0193049.s001 chicago: Bod’Ová, Katarína, Gabriel Mitchell, Roy Harpaz, Elad Schneidman, and Gašper Tkačik. “Implementation of the Inference Method in Matlab.” Public Library of Science, 2018. https://doi.org/10.1371/journal.pone.0193049.s001. ieee: K. Bod’Ová, G. Mitchell, R. Harpaz, E. Schneidman, and G. Tkačik, “Implementation of the inference method in Matlab.” Public Library of Science, 2018. ista: Bod’Ová K, Mitchell G, Harpaz R, Schneidman E, Tkačik G. 2018. Implementation of the inference method in Matlab, Public Library of Science, 10.1371/journal.pone.0193049.s001. mla: Bod’Ová, Katarína, et al. Implementation of the Inference Method in Matlab. Public Library of Science, 2018, doi:10.1371/journal.pone.0193049.s001. short: K. Bod’Ová, G. Mitchell, R. Harpaz, E. Schneidman, G. Tkačik, (2018). date_created: 2021-08-09T07:01:24Z date_published: 2018-03-07T00:00:00Z date_updated: 2023-09-15T12:06:18Z day: '07' department: - _id: GaTk doi: 10.1371/journal.pone.0193049.s001 month: '03' oa_version: Published Version publisher: Public Library of Science related_material: record: - id: '406' relation: used_in_publication status: public status: public title: Implementation of the inference method in Matlab type: research_data_reference user_id: 6785fbc1-c503-11eb-8a32-93094b40e1cf year: '2018' ... --- _id: '31' abstract: - lang: eng text: Correlations in sensory neural networks have both extrinsic and intrinsic origins. Extrinsic or stimulus correlations arise from shared inputs to the network and, thus, depend strongly on the stimulus ensemble. Intrinsic or noise correlations reflect biophysical mechanisms of interactions between neurons, which are expected to be robust to changes in the stimulus ensemble. Despite the importance of this distinction for understanding how sensory networks encode information collectively, no method exists to reliably separate intrinsic interactions from extrinsic correlations in neural activity data, limiting our ability to build predictive models of the network response. In this paper we introduce a general strategy to infer population models of interacting neurons that collectively encode stimulus information. The key to disentangling intrinsic from extrinsic correlations is to infer the couplings between neurons separately from the encoding model and to combine the two using corrections calculated in a mean-field approximation. We demonstrate the effectiveness of this approach in retinal recordings. The same coupling network is inferred from responses to radically different stimulus ensembles, showing that these couplings indeed reflect stimulus-independent interactions between neurons. The inferred model predicts accurately the collective response of retinal ganglion cell populations as a function of the stimulus. acknowledgement: This work was supported by ANR Trajectory, the French State program Investissements d’Avenir managed by the Agence Nationale de la Recherche (LIFESENSES; ANR-10-LABX-65), EC Grant No. H2020-785907 from the Human Brain Project, NIH Grant No. U01NS090501, and an AVIESAN-UNADEV grant to O.M. M.C. was supported by the Agence Nationale de la Recherche Jeune Chercheur/Jeune Chercheuse grant (ANR-17-CE37-0013). article_number: '042410' article_processing_charge: No article_type: original author: - first_name: Ulisse full_name: Ferrari, Ulisse last_name: Ferrari - first_name: Stephane full_name: Deny, Stephane last_name: Deny - first_name: Matthew J full_name: Chalk, Matthew J last_name: Chalk - first_name: Gasper full_name: Tkacik, Gasper id: 3D494DCA-F248-11E8-B48F-1D18A9856A87 last_name: Tkacik orcid: 0000-0002-6699-1455 - first_name: Olivier full_name: Marre, Olivier last_name: Marre - first_name: Thierry full_name: Mora, Thierry last_name: Mora citation: ama: Ferrari U, Deny S, Chalk MJ, Tkačik G, Marre O, Mora T. Separating intrinsic interactions from extrinsic correlations in a network of sensory neurons. Physical Review E. 2018;98(4). doi:10.1103/PhysRevE.98.042410 apa: Ferrari, U., Deny, S., Chalk, M. J., Tkačik, G., Marre, O., & Mora, T. (2018). Separating intrinsic interactions from extrinsic correlations in a network of sensory neurons. Physical Review E. American Physical Society. https://doi.org/10.1103/PhysRevE.98.042410 chicago: Ferrari, Ulisse, Stephane Deny, Matthew J Chalk, Gašper Tkačik, Olivier Marre, and Thierry Mora. “Separating Intrinsic Interactions from Extrinsic Correlations in a Network of Sensory Neurons.” Physical Review E. American Physical Society, 2018. https://doi.org/10.1103/PhysRevE.98.042410. ieee: U. Ferrari, S. Deny, M. J. Chalk, G. Tkačik, O. Marre, and T. Mora, “Separating intrinsic interactions from extrinsic correlations in a network of sensory neurons,” Physical Review E, vol. 98, no. 4. American Physical Society, 2018. ista: Ferrari U, Deny S, Chalk MJ, Tkačik G, Marre O, Mora T. 2018. Separating intrinsic interactions from extrinsic correlations in a network of sensory neurons. Physical Review E. 98(4), 042410. mla: Ferrari, Ulisse, et al. “Separating Intrinsic Interactions from Extrinsic Correlations in a Network of Sensory Neurons.” Physical Review E, vol. 98, no. 4, 042410, American Physical Society, 2018, doi:10.1103/PhysRevE.98.042410. short: U. Ferrari, S. Deny, M.J. Chalk, G. Tkačik, O. Marre, T. Mora, Physical Review E 98 (2018). date_created: 2018-12-11T11:44:15Z date_published: 2018-10-17T00:00:00Z date_updated: 2023-09-18T09:18:44Z day: '17' department: - _id: GaTk doi: 10.1103/PhysRevE.98.042410 ec_funded: 1 external_id: isi: - '000447486100004' intvolume: ' 98' isi: 1 issue: '4' language: - iso: eng main_file_link: - open_access: '1' url: https://www.biorxiv.org/content/10.1101/243816v2.full month: '10' oa: 1 oa_version: Preprint project: - _id: 26436750-B435-11E9-9278-68D0E5697425 call_identifier: H2020 grant_number: '785907' name: Human Brain Project Specific Grant Agreement 2 (HBP SGA 2) publication: Physical Review E publication_identifier: issn: - '24700045' publication_status: published publisher: American Physical Society publist_id: '8024' quality_controlled: '1' scopus_import: '1' status: public title: Separating intrinsic interactions from extrinsic correlations in a network of sensory neurons type: journal_article user_id: c635000d-4b10-11ee-a964-aac5a93f6ac1 volume: 98 year: '2018' ... --- _id: '543' abstract: - lang: eng text: A central goal in theoretical neuroscience is to predict the response properties of sensory neurons from first principles. To this end, “efficient coding” posits that sensory neurons encode maximal information about their inputs given internal constraints. There exist, however, many variants of efficient coding (e.g., redundancy reduction, different formulations of predictive coding, robust coding, sparse coding, etc.), differing in their regimes of applicability, in the relevance of signals to be encoded, and in the choice of constraints. It is unclear how these types of efficient coding relate or what is expected when different coding objectives are combined. Here we present a unified framework that encompasses previously proposed efficient coding models and extends to unique regimes. We show that optimizing neural responses to encode predictive information can lead them to either correlate or decorrelate their inputs, depending on the stimulus statistics; in contrast, at low noise, efficiently encoding the past always predicts decorrelation. Later, we investigate coding of naturalistic movies and show that qualitatively different types of visual motion tuning and levels of response sparsity are predicted, depending on whether the objective is to recover the past or predict the future. Our approach promises a way to explain the observed diversity of sensory neural responses, as due to multiple functional goals and constraints fulfilled by different cell types and/or circuits. article_processing_charge: No author: - first_name: Matthew J full_name: Chalk, Matthew J id: 2BAAC544-F248-11E8-B48F-1D18A9856A87 last_name: Chalk orcid: 0000-0001-7782-4436 - first_name: Olivier full_name: Marre, Olivier last_name: Marre - first_name: Gasper full_name: Tkacik, Gasper id: 3D494DCA-F248-11E8-B48F-1D18A9856A87 last_name: Tkacik orcid: 0000-0002-6699-1455 citation: ama: Chalk MJ, Marre O, Tkačik G. Toward a unified theory of efficient, predictive, and sparse coding. PNAS. 2018;115(1):186-191. doi:10.1073/pnas.1711114115 apa: Chalk, M. J., Marre, O., & Tkačik, G. (2018). Toward a unified theory of efficient, predictive, and sparse coding. PNAS. National Academy of Sciences. https://doi.org/10.1073/pnas.1711114115 chicago: Chalk, Matthew J, Olivier Marre, and Gašper Tkačik. “Toward a Unified Theory of Efficient, Predictive, and Sparse Coding.” PNAS. National Academy of Sciences, 2018. https://doi.org/10.1073/pnas.1711114115. ieee: M. J. Chalk, O. Marre, and G. Tkačik, “Toward a unified theory of efficient, predictive, and sparse coding,” PNAS, vol. 115, no. 1. National Academy of Sciences, pp. 186–191, 2018. ista: Chalk MJ, Marre O, Tkačik G. 2018. Toward a unified theory of efficient, predictive, and sparse coding. PNAS. 115(1), 186–191. mla: Chalk, Matthew J., et al. “Toward a Unified Theory of Efficient, Predictive, and Sparse Coding.” PNAS, vol. 115, no. 1, National Academy of Sciences, 2018, pp. 186–91, doi:10.1073/pnas.1711114115. short: M.J. Chalk, O. Marre, G. Tkačik, PNAS 115 (2018) 186–191. date_created: 2018-12-11T11:47:04Z date_published: 2018-01-02T00:00:00Z date_updated: 2023-09-19T10:16:35Z day: '02' department: - _id: GaTk doi: 10.1073/pnas.1711114115 external_id: isi: - '000419128700049' intvolume: ' 115' isi: 1 issue: '1' language: - iso: eng main_file_link: - open_access: '1' url: 'https://doi.org/10.1101/152660 ' month: '01' oa: 1 oa_version: Submitted Version page: 186 - 191 project: - _id: 254D1A94-B435-11E9-9278-68D0E5697425 call_identifier: FWF grant_number: P 25651-N26 name: Sensitivity to higher-order statistics in natural scenes publication: PNAS publication_status: published publisher: National Academy of Sciences publist_id: '7273' quality_controlled: '1' scopus_import: '1' status: public title: Toward a unified theory of efficient, predictive, and sparse coding type: journal_article user_id: c635000d-4b10-11ee-a964-aac5a93f6ac1 volume: 115 year: '2018' ... --- _id: '607' abstract: - lang: eng text: We study the Fokker-Planck equation derived in the large system limit of the Markovian process describing the dynamics of quantitative traits. The Fokker-Planck equation is posed on a bounded domain and its transport and diffusion coefficients vanish on the domain's boundary. We first argue that, despite this degeneracy, the standard no-flux boundary condition is valid. We derive the weak formulation of the problem and prove the existence and uniqueness of its solutions by constructing the corresponding contraction semigroup on a suitable function space. Then, we prove that for the parameter regime with high enough mutation rate the problem exhibits a positive spectral gap, which implies exponential convergence to equilibrium.Next, we provide a simple derivation of the so-called Dynamic Maximum Entropy (DynMaxEnt) method for approximation of observables (moments) of the Fokker-Planck solution, which can be interpreted as a nonlinear Galerkin approximation. The limited applicability of the DynMaxEnt method inspires us to introduce its modified version that is valid for the whole range of admissible parameters. Finally, we present several numerical experiments to demonstrate the performance of both the original and modified DynMaxEnt methods. We observe that in the parameter regimes where both methods are valid, the modified one exhibits slightly better approximation properties compared to the original one. acknowledgement: "JH and PM are funded by KAUST baseline funds and grant no. 1000000193 .\r\nWe thank Nicholas Barton (IST Austria) for his useful comments and suggestions. \r\n\r\n" article_processing_charge: No author: - first_name: Katarina full_name: Bodova, Katarina id: 2BA24EA0-F248-11E8-B48F-1D18A9856A87 last_name: Bodova orcid: 0000-0002-7214-0171 - first_name: Jan full_name: Haskovec, Jan last_name: Haskovec - first_name: Peter full_name: Markowich, Peter last_name: Markowich citation: ama: 'Bodova K, Haskovec J, Markowich P. Well posedness and maximum entropy approximation for the dynamics of quantitative traits. Physica D: Nonlinear Phenomena. 2018;376-377:108-120. doi:10.1016/j.physd.2017.10.015' apa: 'Bodova, K., Haskovec, J., & Markowich, P. (2018). Well posedness and maximum entropy approximation for the dynamics of quantitative traits. Physica D: Nonlinear Phenomena. Elsevier. https://doi.org/10.1016/j.physd.2017.10.015' chicago: 'Bodova, Katarina, Jan Haskovec, and Peter Markowich. “Well Posedness and Maximum Entropy Approximation for the Dynamics of Quantitative Traits.” Physica D: Nonlinear Phenomena. Elsevier, 2018. https://doi.org/10.1016/j.physd.2017.10.015.' ieee: 'K. Bodova, J. Haskovec, and P. Markowich, “Well posedness and maximum entropy approximation for the dynamics of quantitative traits,” Physica D: Nonlinear Phenomena, vol. 376–377. Elsevier, pp. 108–120, 2018.' ista: 'Bodova K, Haskovec J, Markowich P. 2018. Well posedness and maximum entropy approximation for the dynamics of quantitative traits. Physica D: Nonlinear Phenomena. 376–377, 108–120.' mla: 'Bodova, Katarina, et al. “Well Posedness and Maximum Entropy Approximation for the Dynamics of Quantitative Traits.” Physica D: Nonlinear Phenomena, vol. 376–377, Elsevier, 2018, pp. 108–20, doi:10.1016/j.physd.2017.10.015.' short: 'K. Bodova, J. Haskovec, P. Markowich, Physica D: Nonlinear Phenomena 376–377 (2018) 108–120.' date_created: 2018-12-11T11:47:28Z date_published: 2018-08-01T00:00:00Z date_updated: 2023-09-19T10:38:34Z day: '01' department: - _id: NiBa - _id: GaTk doi: 10.1016/j.physd.2017.10.015 external_id: arxiv: - '1704.08757' isi: - '000437962900012' isi: 1 language: - iso: eng main_file_link: - open_access: '1' url: https://arxiv.org/abs/1704.08757 month: '08' oa: 1 oa_version: Submitted Version page: 108-120 publication: 'Physica D: Nonlinear Phenomena' publication_status: published publisher: Elsevier publist_id: '7198' quality_controlled: '1' scopus_import: '1' status: public title: Well posedness and maximum entropy approximation for the dynamics of quantitative traits type: journal_article user_id: c635000d-4b10-11ee-a964-aac5a93f6ac1 volume: 376-377 year: '2018' ... --- _id: '19' abstract: - lang: eng text: Bacteria regulate genes to survive antibiotic stress, but regulation can be far from perfect. When regulation is not optimal, mutations that change gene expression can contribute to antibiotic resistance. It is not systematically understood to what extent natural gene regulation is or is not optimal for distinct antibiotics, and how changes in expression of specific genes quantitatively affect antibiotic resistance. Here we discover a simple quantitative relation between fitness, gene expression, and antibiotic potency, which rationalizes our observation that a multitude of genes and even innate antibiotic defense mechanisms have expression that is critically nonoptimal under antibiotic treatment. First, we developed a pooled-strain drug-diffusion assay and screened Escherichia coli overexpression and knockout libraries, finding that resistance to a range of 31 antibiotics could result from changing expression of a large and functionally diverse set of genes, in a primarily but not exclusively drug-specific manner. Second, by synthetically controlling the expression of single-drug and multidrug resistance genes, we observed that their fitness-expression functions changed dramatically under antibiotic treatment in accordance with a log-sensitivity relation. Thus, because many genes are nonoptimally expressed under antibiotic treatment, many regulatory mutations can contribute to resistance by altering expression and by activating latent defenses. article_processing_charge: No article_type: original author: - first_name: Adam full_name: Palmer, Adam last_name: Palmer - first_name: Remy P full_name: Chait, Remy P id: 3464AE84-F248-11E8-B48F-1D18A9856A87 last_name: Chait orcid: 0000-0003-0876-3187 - first_name: Roy full_name: Kishony, Roy last_name: Kishony citation: ama: Palmer A, Chait RP, Kishony R. Nonoptimal gene expression creates latent potential for antibiotic resistance. Molecular Biology and Evolution. 2018;35(11):2669-2684. doi:10.1093/molbev/msy163 apa: Palmer, A., Chait, R. P., & Kishony, R. (2018). Nonoptimal gene expression creates latent potential for antibiotic resistance. Molecular Biology and Evolution. Oxford University Press. https://doi.org/10.1093/molbev/msy163 chicago: Palmer, Adam, Remy P Chait, and Roy Kishony. “Nonoptimal Gene Expression Creates Latent Potential for Antibiotic Resistance.” Molecular Biology and Evolution. Oxford University Press, 2018. https://doi.org/10.1093/molbev/msy163. ieee: A. Palmer, R. P. Chait, and R. Kishony, “Nonoptimal gene expression creates latent potential for antibiotic resistance,” Molecular Biology and Evolution, vol. 35, no. 11. Oxford University Press, pp. 2669–2684, 2018. ista: Palmer A, Chait RP, Kishony R. 2018. Nonoptimal gene expression creates latent potential for antibiotic resistance. Molecular Biology and Evolution. 35(11), 2669–2684. mla: Palmer, Adam, et al. “Nonoptimal Gene Expression Creates Latent Potential for Antibiotic Resistance.” Molecular Biology and Evolution, vol. 35, no. 11, Oxford University Press, 2018, pp. 2669–84, doi:10.1093/molbev/msy163. short: A. Palmer, R.P. Chait, R. Kishony, Molecular Biology and Evolution 35 (2018) 2669–2684. date_created: 2018-12-11T11:44:11Z date_published: 2018-08-28T00:00:00Z date_updated: 2023-10-17T11:51:06Z day: '28' department: - _id: CaGu - _id: GaTk doi: 10.1093/molbev/msy163 external_id: isi: - '000452567200006' pmid: - '30169679' intvolume: ' 35' isi: 1 issue: '11' language: - iso: eng main_file_link: - open_access: '1' url: https://www.ncbi.nlm.nih.gov/pubmed/30169679 month: '08' oa: 1 oa_version: Submitted Version page: 2669 - 2684 pmid: 1 publication: Molecular Biology and Evolution publication_identifier: issn: - 0737-4038 publication_status: published publisher: Oxford University Press publist_id: '8036' quality_controlled: '1' scopus_import: '1' status: public title: Nonoptimal gene expression creates latent potential for antibiotic resistance type: journal_article user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87 volume: 35 year: '2018' ... --- _id: '292' abstract: - lang: eng text: 'Retina is a paradigmatic system for studying sensory encoding: the transformation of light into spiking activity of ganglion cells. The inverse problem, where stimulus is reconstructed from spikes, has received less attention, especially for complex stimuli that should be reconstructed “pixel-by-pixel”. We recorded around a hundred neurons from a dense patch in a rat retina and decoded movies of multiple small randomly-moving discs. We constructed nonlinear (kernelized and neural network) decoders that improved significantly over linear results. An important contribution to this was the ability of nonlinear decoders to reliably separate between neural responses driven by locally fluctuating light signals, and responses at locally constant light driven by spontaneous-like activity. This improvement crucially depended on the precise, non-Poisson temporal structure of individual spike trains, which originated in the spike-history dependence of neural responses. We propose a general principle by which downstream circuitry could discriminate between spontaneous and stimulus-driven activity based solely on higher-order statistical structure in the incoming spike trains.' article_number: e1006057 article_processing_charge: Yes article_type: original author: - first_name: Vicent full_name: Botella Soler, Vicent id: 421234E8-F248-11E8-B48F-1D18A9856A87 last_name: Botella Soler orcid: 0000-0002-8790-1914 - first_name: Stephane full_name: Deny, Stephane last_name: Deny - first_name: Georg S full_name: Martius, Georg S last_name: Martius - first_name: Olivier full_name: Marre, Olivier last_name: Marre - first_name: Gasper full_name: Tkacik, Gasper id: 3D494DCA-F248-11E8-B48F-1D18A9856A87 last_name: Tkacik orcid: 0000-0002-6699-1455 citation: ama: Botella Soler V, Deny S, Martius GS, Marre O, Tkačik G. Nonlinear decoding of a complex movie from the mammalian retina. PLoS Computational Biology. 2018;14(5). doi:10.1371/journal.pcbi.1006057 apa: Botella Soler, V., Deny, S., Martius, G. S., Marre, O., & Tkačik, G. (2018). Nonlinear decoding of a complex movie from the mammalian retina. PLoS Computational Biology. Public Library of Science. https://doi.org/10.1371/journal.pcbi.1006057 chicago: Botella Soler, Vicente, Stephane Deny, Georg S Martius, Olivier Marre, and Gašper Tkačik. “Nonlinear Decoding of a Complex Movie from the Mammalian Retina.” PLoS Computational Biology. Public Library of Science, 2018. https://doi.org/10.1371/journal.pcbi.1006057. ieee: V. Botella Soler, S. Deny, G. S. Martius, O. Marre, and G. Tkačik, “Nonlinear decoding of a complex movie from the mammalian retina,” PLoS Computational Biology, vol. 14, no. 5. Public Library of Science, 2018. ista: Botella Soler V, Deny S, Martius GS, Marre O, Tkačik G. 2018. Nonlinear decoding of a complex movie from the mammalian retina. PLoS Computational Biology. 14(5), e1006057. mla: Botella Soler, Vicente, et al. “Nonlinear Decoding of a Complex Movie from the Mammalian Retina.” PLoS Computational Biology, vol. 14, no. 5, e1006057, Public Library of Science, 2018, doi:10.1371/journal.pcbi.1006057. short: V. Botella Soler, S. Deny, G.S. Martius, O. Marre, G. Tkačik, PLoS Computational Biology 14 (2018). date_created: 2018-12-11T11:45:39Z date_published: 2018-05-10T00:00:00Z date_updated: 2024-02-21T13:45:25Z day: '10' ddc: - '570' department: - _id: GaTk doi: 10.1371/journal.pcbi.1006057 ec_funded: 1 external_id: isi: - '000434012100002' file: - access_level: open_access checksum: 3026f94d235219e15514505fdbadf34e content_type: application/pdf creator: dernst date_created: 2019-02-13T11:07:15Z date_updated: 2020-07-14T12:45:53Z file_id: '5974' file_name: 2018_Plos_Botella_Soler.pdf file_size: 3460786 relation: main_file file_date_updated: 2020-07-14T12:45:53Z has_accepted_license: '1' intvolume: ' 14' isi: 1 issue: '5' language: - iso: eng month: '05' oa: 1 oa_version: Published Version project: - _id: 25CBA828-B435-11E9-9278-68D0E5697425 call_identifier: H2020 grant_number: '720270' name: Human Brain Project Specific Grant Agreement 1 (HBP SGA 1) - _id: 254D1A94-B435-11E9-9278-68D0E5697425 call_identifier: FWF grant_number: P 25651-N26 name: Sensitivity to higher-order statistics in natural scenes publication: PLoS Computational Biology publication_status: published publisher: Public Library of Science quality_controlled: '1' related_material: link: - description: News on IST Homepage relation: press_release url: https://ist.ac.at/en/news/video-of-moving-discs-reconstructed-from-rat-retinal-neuron-signals/ record: - id: '5584' relation: research_data status: public scopus_import: '1' status: public title: Nonlinear decoding of a complex movie from the mammalian retina tmp: image: /images/cc_by.png legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0) short: CC BY (4.0) type: journal_article user_id: c635000d-4b10-11ee-a964-aac5a93f6ac1 volume: 14 year: '2018' ... --- _id: '5584' abstract: - lang: eng text: "This package contains data for the publication \"Nonlinear decoding of a complex movie from the mammalian retina\" by Deny S. et al, PLOS Comput Biol (2018). \r\n\r\nThe data consists of\r\n(i) 91 spike sorted, isolated rat retinal ganglion cells that pass stability and quality criteria, recorded on the multi-electrode array, in response to the presentation of the complex movie with many randomly moving dark discs. The responses are represented as 648000 x 91 binary matrix, where the first index indicates the timebin of duration 12.5 ms, and the second index the neural identity. The matrix entry is 0/1 if the neuron didn't/did spike in the particular time bin.\r\n(ii) README file and a graphical illustration of the structure of the experiment, specifying how the 648000 timebins are split into epochs where 1, 2, 4, or 10 discs were displayed, and which stimulus segments are exact repeats or unique ball trajectories.\r\n(iii) a 648000 x 400 matrix of luminance traces for each of the 20 x 20 positions (\"sites\") in the movie frame, with time that is locked to the recorded raster. The luminance traces are produced as described in the manuscript by filtering the raw disc movie with a small gaussian spatial kernel. " article_processing_charge: No author: - first_name: Stephane full_name: Deny, Stephane last_name: Deny - first_name: Olivier full_name: Marre, Olivier last_name: Marre - first_name: Vicente full_name: Botella-Soler, Vicente last_name: Botella-Soler - first_name: Georg S full_name: Martius, Georg S id: 3A276B68-F248-11E8-B48F-1D18A9856A87 last_name: Martius - first_name: Gasper full_name: Tkacik, Gasper id: 3D494DCA-F248-11E8-B48F-1D18A9856A87 last_name: Tkacik orcid: 0000-0002-6699-1455 citation: ama: Deny S, Marre O, Botella-Soler V, Martius GS, Tkačik G. Nonlinear decoding of a complex movie from the mammalian retina. 2018. doi:10.15479/AT:ISTA:98 apa: Deny, S., Marre, O., Botella-Soler, V., Martius, G. S., & Tkačik, G. (2018). Nonlinear decoding of a complex movie from the mammalian retina. Institute of Science and Technology Austria. https://doi.org/10.15479/AT:ISTA:98 chicago: Deny, Stephane, Olivier Marre, Vicente Botella-Soler, Georg S Martius, and Gašper Tkačik. “Nonlinear Decoding of a Complex Movie from the Mammalian Retina.” Institute of Science and Technology Austria, 2018. https://doi.org/10.15479/AT:ISTA:98. ieee: S. Deny, O. Marre, V. Botella-Soler, G. S. Martius, and G. Tkačik, “Nonlinear decoding of a complex movie from the mammalian retina.” Institute of Science and Technology Austria, 2018. ista: Deny S, Marre O, Botella-Soler V, Martius GS, Tkačik G. 2018. Nonlinear decoding of a complex movie from the mammalian retina, Institute of Science and Technology Austria, 10.15479/AT:ISTA:98. mla: Deny, Stephane, et al. Nonlinear Decoding of a Complex Movie from the Mammalian Retina. Institute of Science and Technology Austria, 2018, doi:10.15479/AT:ISTA:98. short: S. Deny, O. Marre, V. Botella-Soler, G.S. Martius, G. Tkačik, (2018). datarep_id: '98' date_created: 2018-12-12T12:31:39Z date_published: 2018-03-29T00:00:00Z date_updated: 2024-02-21T13:45:26Z day: '29' ddc: - '570' department: - _id: ChLa - _id: GaTk doi: 10.15479/AT:ISTA:98 file: - access_level: open_access checksum: 6808748837b9afbbbabc2a356ca2b88a content_type: application/octet-stream creator: system date_created: 2018-12-12T13:02:24Z date_updated: 2020-07-14T12:47:07Z file_id: '5590' file_name: IST-2018-98-v1+1_BBalls_area2_tile2_20x20.mat file_size: 1142543971 relation: main_file - access_level: open_access checksum: d6d6cd07743038fe3a12352983fcf9dd content_type: application/pdf creator: system date_created: 2018-12-12T13:02:25Z date_updated: 2020-07-14T12:47:07Z file_id: '5591' file_name: IST-2018-98-v1+2_ExperimentStructure.pdf file_size: 702336 relation: main_file - access_level: open_access checksum: 0c9cfb4dab35bb3dc25a04395600b1c8 content_type: application/octet-stream creator: system date_created: 2018-12-12T13:02:26Z date_updated: 2020-07-14T12:47:07Z file_id: '5592' file_name: IST-2018-98-v1+3_GoodLocations_area2_20x20.mat file_size: 432 relation: main_file - access_level: open_access checksum: 2a83b011012e21e934b4596285b1a183 content_type: text/plain creator: system date_created: 2018-12-12T13:02:26Z date_updated: 2020-07-14T12:47:07Z file_id: '5593' file_name: IST-2018-98-v1+4_README.txt file_size: 986 relation: main_file file_date_updated: 2020-07-14T12:47:07Z has_accepted_license: '1' keyword: - retina - decoding - regression - neural networks - complex stimulus license: https://creativecommons.org/publicdomain/zero/1.0/ month: '03' oa: 1 oa_version: Published Version project: - _id: 254D1A94-B435-11E9-9278-68D0E5697425 call_identifier: FWF grant_number: P 25651-N26 name: Sensitivity to higher-order statistics in natural scenes publisher: Institute of Science and Technology Austria related_material: record: - id: '292' relation: used_in_publication status: public status: public title: Nonlinear decoding of a complex movie from the mammalian retina tmp: image: /images/cc_0.png legal_code_url: https://creativecommons.org/publicdomain/zero/1.0/legalcode name: Creative Commons Public Domain Dedication (CC0 1.0) short: CC0 (1.0) type: research_data user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87 year: '2018' ... --- _id: '161' abstract: - lang: eng text: 'Which properties of metabolic networks can be derived solely from stoichiometry? Predictive results have been obtained by flux balance analysis (FBA), by postulating that cells set metabolic fluxes to maximize growth rate. Here we consider a generalization of FBA to single-cell level using maximum entropy modeling, which we extend and test experimentally. Specifically, we define for Escherichia coli metabolism a flux distribution that yields the experimental growth rate: the model, containing FBA as a limit, provides a better match to measured fluxes and it makes a wide range of predictions: on flux variability, regulation, and correlations; on the relative importance of stoichiometry vs. optimization; on scaling relations for growth rate distributions. We validate the latter here with single-cell data at different sub-inhibitory antibiotic concentrations. The model quantifies growth optimization as emerging from the interplay of competitive dynamics in the population and regulation of metabolism at the level of single cells.' article_number: '2988' article_processing_charge: No author: - first_name: Daniele full_name: De Martino, Daniele id: 3FF5848A-F248-11E8-B48F-1D18A9856A87 last_name: De Martino orcid: 0000-0002-5214-4706 - first_name: Andersson Anna full_name: Mc, Andersson Anna last_name: Mc - first_name: Tobias full_name: Bergmiller, Tobias id: 2C471CFA-F248-11E8-B48F-1D18A9856A87 last_name: Bergmiller orcid: 0000-0001-5396-4346 - first_name: Calin C full_name: Guet, Calin C id: 47F8433E-F248-11E8-B48F-1D18A9856A87 last_name: Guet orcid: 0000-0001-6220-2052 - first_name: Gasper full_name: Tkacik, Gasper id: 3D494DCA-F248-11E8-B48F-1D18A9856A87 last_name: Tkacik orcid: 0000-0002-6699-1455 citation: ama: De Martino D, Mc AA, Bergmiller T, Guet CC, Tkačik G. Statistical mechanics for metabolic networks during steady state growth. Nature Communications. 2018;9(1). doi:10.1038/s41467-018-05417-9 apa: De Martino, D., Mc, A. A., Bergmiller, T., Guet, C. C., & Tkačik, G. (2018). Statistical mechanics for metabolic networks during steady state growth. Nature Communications. Springer Nature. https://doi.org/10.1038/s41467-018-05417-9 chicago: De Martino, Daniele, Andersson Anna Mc, Tobias Bergmiller, Calin C Guet, and Gašper Tkačik. “Statistical Mechanics for Metabolic Networks during Steady State Growth.” Nature Communications. Springer Nature, 2018. https://doi.org/10.1038/s41467-018-05417-9. ieee: D. De Martino, A. A. Mc, T. Bergmiller, C. C. Guet, and G. Tkačik, “Statistical mechanics for metabolic networks during steady state growth,” Nature Communications, vol. 9, no. 1. Springer Nature, 2018. ista: De Martino D, Mc AA, Bergmiller T, Guet CC, Tkačik G. 2018. Statistical mechanics for metabolic networks during steady state growth. Nature Communications. 9(1), 2988. mla: De Martino, Daniele, et al. “Statistical Mechanics for Metabolic Networks during Steady State Growth.” Nature Communications, vol. 9, no. 1, 2988, Springer Nature, 2018, doi:10.1038/s41467-018-05417-9. short: D. De Martino, A.A. Mc, T. Bergmiller, C.C. Guet, G. Tkačik, Nature Communications 9 (2018). date_created: 2018-12-11T11:44:57Z date_published: 2018-07-30T00:00:00Z date_updated: 2024-02-21T13:45:39Z day: '30' ddc: - '570' department: - _id: GaTk - _id: CaGu doi: 10.1038/s41467-018-05417-9 ec_funded: 1 external_id: isi: - '000440149300021' file: - access_level: open_access checksum: 3ba7ab27b27723c7dcf633e8fc1f8f18 content_type: application/pdf creator: dernst date_created: 2018-12-17T16:44:28Z date_updated: 2020-07-14T12:45:06Z file_id: '5728' file_name: 2018_NatureComm_DeMartino.pdf file_size: 1043205 relation: main_file file_date_updated: 2020-07-14T12:45:06Z has_accepted_license: '1' intvolume: ' 9' isi: 1 issue: '1' language: - iso: eng month: '07' oa: 1 oa_version: Published Version project: - _id: 254E9036-B435-11E9-9278-68D0E5697425 call_identifier: FWF grant_number: P28844-B27 name: Biophysics of information processing in gene regulation - _id: 25681D80-B435-11E9-9278-68D0E5697425 call_identifier: FP7 grant_number: '291734' name: International IST Postdoc Fellowship Programme publication: Nature Communications publication_status: published publisher: Springer Nature publist_id: '7760' quality_controlled: '1' related_material: record: - id: '5587' relation: popular_science status: public scopus_import: '1' status: public title: Statistical mechanics for metabolic networks during steady state growth tmp: image: /images/cc_by.png legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0) short: CC BY (4.0) type: journal_article user_id: c635000d-4b10-11ee-a964-aac5a93f6ac1 volume: 9 year: '2018' ... --- _id: '5587' abstract: - lang: eng text: "Supporting material to the article \r\nSTATISTICAL MECHANICS FOR METABOLIC NETWORKS IN STEADY-STATE GROWTH\r\n\r\nboundscoli.dat\r\nFlux Bounds of the E. coli catabolic core model iAF1260 in a glucose limited minimal medium. \r\n\r\npolcoli.dat\r\nMatrix enconding the polytope of the E. coli catabolic core model iAF1260 in a glucose limited minimal medium, \r\nobtained from the soichiometric matrix by standard linear algebra (reduced row echelon form).\r\n\r\nellis.dat\r\nApproximate Lowner-John ellipsoid rounding the polytope of the E. coli catabolic core model iAF1260 in a glucose limited minimal medium\r\nobtained with the Lovasz method.\r\n\r\npoint0.dat\r\nCenter of the approximate Lowner-John ellipsoid rounding the polytope of the E. coli catabolic core model iAF1260 in a glucose limited minimal medium\r\nobtained with the Lovasz method.\r\n\r\nlovasz.cpp \r\nThis c++ code file receives in input the polytope of the feasible steady states of a metabolic network, \r\n(matrix and bounds), and it gives in output an approximate Lowner-John ellipsoid rounding the polytope\r\nwith the Lovasz method \r\nNB inputs are referred by defaults to the catabolic core of the E.Coli network iAF1260. \r\nFor further details we refer to PLoS ONE 10.4 e0122670 (2015).\r\n\r\nsampleHRnew.cpp \r\nThis c++ code file receives in input the polytope of the feasible steady states of a metabolic network, \r\n(matrix and bounds), the ellipsoid rounding the polytope, a point inside and \r\nit gives in output a max entropy sampling at fixed average growth rate \r\nof the steady states by performing an Hit-and-Run Monte Carlo Markov chain.\r\nNB inputs are referred by defaults to the catabolic core of the E.Coli network iAF1260. \r\nFor further details we refer to PLoS ONE 10.4 e0122670 (2015)." article_processing_charge: No author: - first_name: Daniele full_name: De Martino, Daniele id: 3FF5848A-F248-11E8-B48F-1D18A9856A87 last_name: De Martino orcid: 0000-0002-5214-4706 - first_name: Gasper full_name: Tkacik, Gasper id: 3D494DCA-F248-11E8-B48F-1D18A9856A87 last_name: Tkacik orcid: 0000-0002-6699-1455 citation: ama: De Martino D, Tkačik G. Supporting materials “STATISTICAL MECHANICS FOR METABOLIC NETWORKS IN STEADY-STATE GROWTH.” 2018. doi:10.15479/AT:ISTA:62 apa: De Martino, D., & Tkačik, G. (2018). Supporting materials “STATISTICAL MECHANICS FOR METABOLIC NETWORKS IN STEADY-STATE GROWTH.” Institute of Science and Technology Austria. https://doi.org/10.15479/AT:ISTA:62 chicago: De Martino, Daniele, and Gašper Tkačik. “Supporting Materials ‘STATISTICAL MECHANICS FOR METABOLIC NETWORKS IN STEADY-STATE GROWTH.’” Institute of Science and Technology Austria, 2018. https://doi.org/10.15479/AT:ISTA:62. ieee: D. De Martino and G. Tkačik, “Supporting materials ‘STATISTICAL MECHANICS FOR METABOLIC NETWORKS IN STEADY-STATE GROWTH.’” Institute of Science and Technology Austria, 2018. ista: De Martino D, Tkačik G. 2018. Supporting materials ‘STATISTICAL MECHANICS FOR METABOLIC NETWORKS IN STEADY-STATE GROWTH’, Institute of Science and Technology Austria, 10.15479/AT:ISTA:62. mla: De Martino, Daniele, and Gašper Tkačik. Supporting Materials “STATISTICAL MECHANICS FOR METABOLIC NETWORKS IN STEADY-STATE GROWTH.” Institute of Science and Technology Austria, 2018, doi:10.15479/AT:ISTA:62. short: D. De Martino, G. Tkačik, (2018). datarep_id: '111' date_created: 2018-12-12T12:31:41Z date_published: 2018-09-21T00:00:00Z date_updated: 2024-02-21T13:45:39Z day: '21' ddc: - '530' department: - _id: GaTk doi: 10.15479/AT:ISTA:62 ec_funded: 1 file: - access_level: open_access checksum: 97992e3e8cf8544ec985a48971708726 content_type: application/zip creator: system date_created: 2018-12-12T13:05:13Z date_updated: 2020-07-14T12:47:08Z file_id: '5641' file_name: IST-2018-111-v1+1_CODES.zip file_size: 14376 relation: main_file file_date_updated: 2020-07-14T12:47:08Z has_accepted_license: '1' keyword: - metabolic networks - e.coli core - maximum entropy - monte carlo markov chain sampling - ellipsoidal rounding month: '09' oa: 1 oa_version: Published Version project: - _id: 25681D80-B435-11E9-9278-68D0E5697425 call_identifier: FP7 grant_number: '291734' name: International IST Postdoc Fellowship Programme - _id: 254E9036-B435-11E9-9278-68D0E5697425 call_identifier: FWF grant_number: P28844-B27 name: Biophysics of information processing in gene regulation publisher: Institute of Science and Technology Austria related_material: record: - id: '161' relation: research_paper status: public status: public title: Supporting materials "STATISTICAL MECHANICS FOR METABOLIC NETWORKS IN STEADY-STATE GROWTH" tmp: image: /images/cc_0.png legal_code_url: https://creativecommons.org/publicdomain/zero/1.0/legalcode name: Creative Commons Public Domain Dedication (CC0 1.0) short: CC0 (1.0) type: research_data user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87 year: '2018' ... --- _id: '67' abstract: - lang: eng text: 'Gene regulatory networks evolve through rewiring of individual components—that is, through changes in regulatory connections. However, the mechanistic basis of regulatory rewiring is poorly understood. Using a canonical gene regulatory system, we quantify the properties of transcription factors that determine the evolutionary potential for rewiring of regulatory connections: robustness, tunability and evolvability. In vivo repression measurements of two repressors at mutated operator sites reveal their contrasting evolutionary potential: while robustness and evolvability were positively correlated, both were in trade-off with tunability. Epistatic interactions between adjacent operators alleviated this trade-off. A thermodynamic model explains how the differences in robustness, tunability and evolvability arise from biophysical characteristics of repressor–DNA binding. The model also uncovers that the energy matrix, which describes how mutations affect repressor–DNA binding, encodes crucial information about the evolutionary potential of a repressor. The biophysical determinants of evolutionary potential for regulatory rewiring constitute a mechanistic framework for understanding network evolution.' article_processing_charge: No article_type: original author: - first_name: Claudia full_name: Igler, Claudia id: 46613666-F248-11E8-B48F-1D18A9856A87 last_name: Igler - first_name: Mato full_name: Lagator, Mato id: 345D25EC-F248-11E8-B48F-1D18A9856A87 last_name: Lagator - first_name: Gasper full_name: Tkacik, Gasper id: 3D494DCA-F248-11E8-B48F-1D18A9856A87 last_name: Tkacik orcid: 0000-0002-6699-1455 - first_name: Jonathan P full_name: Bollback, Jonathan P id: 2C6FA9CC-F248-11E8-B48F-1D18A9856A87 last_name: Bollback orcid: 0000-0002-4624-4612 - first_name: Calin C full_name: Guet, Calin C id: 47F8433E-F248-11E8-B48F-1D18A9856A87 last_name: Guet orcid: 0000-0001-6220-2052 citation: ama: Igler C, Lagator M, Tkačik G, Bollback JP, Guet CC. Evolutionary potential of transcription factors for gene regulatory rewiring. Nature Ecology and Evolution. 2018;2(10):1633-1643. doi:10.1038/s41559-018-0651-y apa: Igler, C., Lagator, M., Tkačik, G., Bollback, J. P., & Guet, C. C. (2018). Evolutionary potential of transcription factors for gene regulatory rewiring. Nature Ecology and Evolution. Nature Publishing Group. https://doi.org/10.1038/s41559-018-0651-y chicago: Igler, Claudia, Mato Lagator, Gašper Tkačik, Jonathan P Bollback, and Calin C Guet. “Evolutionary Potential of Transcription Factors for Gene Regulatory Rewiring.” Nature Ecology and Evolution. Nature Publishing Group, 2018. https://doi.org/10.1038/s41559-018-0651-y. ieee: C. Igler, M. Lagator, G. Tkačik, J. P. Bollback, and C. C. Guet, “Evolutionary potential of transcription factors for gene regulatory rewiring,” Nature Ecology and Evolution, vol. 2, no. 10. Nature Publishing Group, pp. 1633–1643, 2018. ista: Igler C, Lagator M, Tkačik G, Bollback JP, Guet CC. 2018. Evolutionary potential of transcription factors for gene regulatory rewiring. Nature Ecology and Evolution. 2(10), 1633–1643. mla: Igler, Claudia, et al. “Evolutionary Potential of Transcription Factors for Gene Regulatory Rewiring.” Nature Ecology and Evolution, vol. 2, no. 10, Nature Publishing Group, 2018, pp. 1633–43, doi:10.1038/s41559-018-0651-y. short: C. Igler, M. Lagator, G. Tkačik, J.P. Bollback, C.C. Guet, Nature Ecology and Evolution 2 (2018) 1633–1643. date_created: 2018-12-11T11:44:27Z date_published: 2018-09-10T00:00:00Z date_updated: 2024-03-27T23:30:48Z day: '10' ddc: - '570' department: - _id: CaGu - _id: GaTk - _id: JoBo doi: 10.1038/s41559-018-0651-y ec_funded: 1 external_id: isi: - '000447947600021' file: - access_level: open_access checksum: 383a2e2c944a856e2e821ec8e7bf71b6 content_type: application/pdf creator: dernst date_created: 2020-05-14T11:28:52Z date_updated: 2020-07-14T12:47:37Z file_id: '7830' file_name: 2018_NatureEcology_Igler.pdf file_size: 1135973 relation: main_file file_date_updated: 2020-07-14T12:47:37Z has_accepted_license: '1' intvolume: ' 2' isi: 1 issue: '10' language: - iso: eng month: '09' oa: 1 oa_version: Submitted Version page: 1633 - 1643 project: - _id: 25681D80-B435-11E9-9278-68D0E5697425 call_identifier: FP7 grant_number: '291734' name: International IST Postdoc Fellowship Programme - _id: 2578D616-B435-11E9-9278-68D0E5697425 call_identifier: H2020 grant_number: '648440' name: Selective Barriers to Horizontal Gene Transfer - _id: 251EE76E-B435-11E9-9278-68D0E5697425 grant_number: '24573' name: Design principles underlying genetic switch architecture (DOC Fellowship) publication: Nature Ecology and Evolution publication_status: published publisher: Nature Publishing Group publist_id: '7987' quality_controlled: '1' related_material: record: - id: '5585' relation: popular_science status: public - id: '6371' relation: dissertation_contains status: public scopus_import: '1' status: public title: Evolutionary potential of transcription factors for gene regulatory rewiring type: journal_article user_id: c635000d-4b10-11ee-a964-aac5a93f6ac1 volume: 2 year: '2018' ... --- _id: '5585' abstract: - lang: eng text: Mean repression values and standard error of the mean are given for all operator mutant libraries. article_processing_charge: No author: - first_name: Claudia full_name: Igler, Claudia id: 46613666-F248-11E8-B48F-1D18A9856A87 last_name: Igler - first_name: Mato full_name: Lagator, Mato id: 345D25EC-F248-11E8-B48F-1D18A9856A87 last_name: Lagator - first_name: Gasper full_name: Tkacik, Gasper id: 3D494DCA-F248-11E8-B48F-1D18A9856A87 last_name: Tkacik orcid: 0000-0002-6699-1455 - first_name: Jonathan P full_name: Bollback, Jonathan P id: 2C6FA9CC-F248-11E8-B48F-1D18A9856A87 last_name: Bollback orcid: 0000-0002-4624-4612 - first_name: Calin C full_name: Guet, Calin C id: 47F8433E-F248-11E8-B48F-1D18A9856A87 last_name: Guet orcid: 0000-0001-6220-2052 citation: ama: Igler C, Lagator M, Tkačik G, Bollback JP, Guet CC. Data for the paper Evolutionary potential of transcription factors for gene regulatory rewiring. 2018. doi:10.15479/AT:ISTA:108 apa: Igler, C., Lagator, M., Tkačik, G., Bollback, J. P., & Guet, C. C. (2018). Data for the paper Evolutionary potential of transcription factors for gene regulatory rewiring. Institute of Science and Technology Austria. https://doi.org/10.15479/AT:ISTA:108 chicago: Igler, Claudia, Mato Lagator, Gašper Tkačik, Jonathan P Bollback, and Calin C Guet. “Data for the Paper Evolutionary Potential of Transcription Factors for Gene Regulatory Rewiring.” Institute of Science and Technology Austria, 2018. https://doi.org/10.15479/AT:ISTA:108. ieee: C. Igler, M. Lagator, G. Tkačik, J. P. Bollback, and C. C. Guet, “Data for the paper Evolutionary potential of transcription factors for gene regulatory rewiring.” Institute of Science and Technology Austria, 2018. ista: Igler C, Lagator M, Tkačik G, Bollback JP, Guet CC. 2018. Data for the paper Evolutionary potential of transcription factors for gene regulatory rewiring, Institute of Science and Technology Austria, 10.15479/AT:ISTA:108. mla: Igler, Claudia, et al. Data for the Paper Evolutionary Potential of Transcription Factors for Gene Regulatory Rewiring. Institute of Science and Technology Austria, 2018, doi:10.15479/AT:ISTA:108. short: C. Igler, M. Lagator, G. Tkačik, J.P. Bollback, C.C. Guet, (2018). datarep_id: '108' date_created: 2018-12-12T12:31:40Z date_published: 2018-07-20T00:00:00Z date_updated: 2024-03-27T23:30:48Z day: '20' ddc: - '576' department: - _id: CaGu - _id: GaTk doi: 10.15479/AT:ISTA:108 ec_funded: 1 file: - access_level: open_access checksum: 1435781526c77413802adee0d4583cce content_type: application/vnd.openxmlformats-officedocument.spreadsheetml.sheet creator: system date_created: 2018-12-12T13:02:45Z date_updated: 2020-07-14T12:47:07Z file_id: '5611' file_name: IST-2018-108-v1+1_data_figures.xlsx file_size: 16507 relation: main_file file_date_updated: 2020-07-14T12:47:07Z has_accepted_license: '1' month: '07' oa: 1 oa_version: Published Version project: - _id: 25681D80-B435-11E9-9278-68D0E5697425 call_identifier: FP7 grant_number: '291734' name: International IST Postdoc Fellowship Programme - _id: 2578D616-B435-11E9-9278-68D0E5697425 call_identifier: H2020 grant_number: '648440' name: Selective Barriers to Horizontal Gene Transfer - _id: 251EE76E-B435-11E9-9278-68D0E5697425 grant_number: '24573' name: Design principles underlying genetic switch architecture (DOC Fellowship) publisher: Institute of Science and Technology Austria related_material: record: - id: '67' relation: research_paper status: public - id: '6371' relation: research_paper status: public status: public title: Data for the paper Evolutionary potential of transcription factors for gene regulatory rewiring tmp: image: /images/cc_0.png legal_code_url: https://creativecommons.org/publicdomain/zero/1.0/legalcode name: Creative Commons Public Domain Dedication (CC0 1.0) short: CC0 (1.0) type: research_data user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87 year: '2018' ... --- _id: '613' abstract: - lang: eng text: 'Bacteria in groups vary individually, and interact with other bacteria and the environment to produce population-level patterns of gene expression. Investigating such behavior in detail requires measuring and controlling populations at the single-cell level alongside precisely specified interactions and environmental characteristics. Here we present an automated, programmable platform that combines image-based gene expression and growth measurements with on-line optogenetic expression control for hundreds of individual Escherichia coli cells over days, in a dynamically adjustable environment. This integrated platform broadly enables experiments that bridge individual and population behaviors. We demonstrate: (i) population structuring by independent closed-loop control of gene expression in many individual cells, (ii) cell-cell variation control during antibiotic perturbation, (iii) hybrid bio-digital circuits in single cells, and freely specifiable digital communication between individual bacteria. These examples showcase the potential for real-time integration of theoretical models with measurement and control of many individual cells to investigate and engineer microbial population behavior.' acknowledgement: We are grateful to M. Lang, H. Janovjak, M. Khammash, A. Milias-Argeitis, M. Rullan, G. Batt, A. Bosma-Moody, Aryan, S. Leibler, and members of the Guet and Tkačik groups for helpful discussion, comments, and suggestions. We thank A. Moglich, T. Mathes, J. Tabor, and S. Schmidl for kind gifts of strains, and R. Hauschild, B. Knep, M. Lang, T. Asenov, E. Papusheva, T. Menner, T. Adletzberger, and J. Merrin for technical assistance. The research leading to these results has received funding from the People Programme (Marie Curie Actions) of the European Union’s Seventh Framework Programme (FP7/2007–2013) under REA grant agreement no. [291734]. (to R.C. and J.R.), Austrian Science Fund grant FWF P28844 (to G.T.), and internal IST Austria Interdisciplinary Project Support. J.R. acknowledges support from the Agence Nationale de la Recherche (ANR) under Grant Nos. ANR-16-CE33-0018 (MEMIP), ANR-16-CE12-0025 (COGEX) and ANR-10-BINF-06-01 (ICEBERG). article_number: '1535' article_processing_charge: Yes (in subscription journal) author: - first_name: Remy P full_name: Chait, Remy P id: 3464AE84-F248-11E8-B48F-1D18A9856A87 last_name: Chait orcid: 0000-0003-0876-3187 - first_name: Jakob full_name: Ruess, Jakob id: 4A245D00-F248-11E8-B48F-1D18A9856A87 last_name: Ruess orcid: 0000-0003-1615-3282 - first_name: Tobias full_name: Bergmiller, Tobias id: 2C471CFA-F248-11E8-B48F-1D18A9856A87 last_name: Bergmiller orcid: 0000-0001-5396-4346 - first_name: Gasper full_name: Tkacik, Gasper id: 3D494DCA-F248-11E8-B48F-1D18A9856A87 last_name: Tkacik orcid: 0000-0002-6699-1455 - first_name: Calin C full_name: Guet, Calin C id: 47F8433E-F248-11E8-B48F-1D18A9856A87 last_name: Guet orcid: 0000-0001-6220-2052 citation: ama: Chait RP, Ruess J, Bergmiller T, Tkačik G, Guet CC. Shaping bacterial population behavior through computer interfaced control of individual cells. Nature Communications. 2017;8(1). doi:10.1038/s41467-017-01683-1 apa: Chait, R. P., Ruess, J., Bergmiller, T., Tkačik, G., & Guet, C. C. (2017). Shaping bacterial population behavior through computer interfaced control of individual cells. Nature Communications. Nature Publishing Group. https://doi.org/10.1038/s41467-017-01683-1 chicago: Chait, Remy P, Jakob Ruess, Tobias Bergmiller, Gašper Tkačik, and Calin C Guet. “Shaping Bacterial Population Behavior through Computer Interfaced Control of Individual Cells.” Nature Communications. Nature Publishing Group, 2017. https://doi.org/10.1038/s41467-017-01683-1. ieee: R. P. Chait, J. Ruess, T. Bergmiller, G. Tkačik, and C. C. Guet, “Shaping bacterial population behavior through computer interfaced control of individual cells,” Nature Communications, vol. 8, no. 1. Nature Publishing Group, 2017. ista: Chait RP, Ruess J, Bergmiller T, Tkačik G, Guet CC. 2017. Shaping bacterial population behavior through computer interfaced control of individual cells. Nature Communications. 8(1), 1535. mla: Chait, Remy P., et al. “Shaping Bacterial Population Behavior through Computer Interfaced Control of Individual Cells.” Nature Communications, vol. 8, no. 1, 1535, Nature Publishing Group, 2017, doi:10.1038/s41467-017-01683-1. short: R.P. Chait, J. Ruess, T. Bergmiller, G. Tkačik, C.C. Guet, Nature Communications 8 (2017). date_created: 2018-12-11T11:47:30Z date_published: 2017-12-01T00:00:00Z date_updated: 2021-01-12T08:06:15Z day: '01' ddc: - '576' - '579' department: - _id: CaGu - _id: GaTk doi: 10.1038/s41467-017-01683-1 ec_funded: 1 file: - access_level: open_access checksum: 44bb5d0229926c23a9955d9fe0f9723f content_type: application/pdf creator: system date_created: 2018-12-12T10:16:05Z date_updated: 2020-07-14T12:47:20Z file_id: '5190' file_name: IST-2017-911-v1+1_s41467-017-01683-1.pdf file_size: 1951699 relation: main_file file_date_updated: 2020-07-14T12:47:20Z has_accepted_license: '1' intvolume: ' 8' issue: '1' language: - iso: eng month: '12' oa: 1 oa_version: Published Version project: - _id: 25681D80-B435-11E9-9278-68D0E5697425 call_identifier: FP7 grant_number: '291734' name: International IST Postdoc Fellowship Programme - _id: 254E9036-B435-11E9-9278-68D0E5697425 call_identifier: FWF grant_number: P28844-B27 name: Biophysics of information processing in gene regulation publication: Nature Communications publication_identifier: issn: - '20411723' publication_status: published publisher: Nature Publishing Group publist_id: '7191' pubrep_id: '911' quality_controlled: '1' scopus_import: 1 status: public title: Shaping bacterial population behavior through computer interfaced control of individual cells tmp: image: /images/cc_by.png legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0) short: CC BY (4.0) type: journal_article user_id: 3E5EF7F0-F248-11E8-B48F-1D18A9856A87 volume: 8 year: '2017' ... --- _id: '652' abstract: - lang: eng text: 'We present an approach that enables robots to self-organize their sensorimotor behavior from scratch without providing specific information about neither the robot nor its environment. This is achieved by a simple neural control law that increases the consistency between external sensor dynamics and internal neural dynamics of the utterly simple controller. In this way, the embodiment and the agent-environment coupling are the only source of individual development. We show how an anthropomorphic tendon driven arm-shoulder system develops different behaviors depending on that coupling. For instance: Given a bottle half-filled with water, the arm starts to shake it, driven by the physical response of the water. When attaching a brush, the arm can be manipulated into wiping a table, and when connected to a revolvable wheel it finds out how to rotate it. Thus, the robot may be said to discover the affordances of the world. When allowing two (simulated) humanoid robots to interact physically, they engage into a joint behavior development leading to, for instance, spontaneous cooperation. More social effects are observed if the robots can visually perceive each other. Although, as an observer, it is tempting to attribute an apparent intentionality, there is nothing of the kind put in. As a conclusion, we argue that emergent behavior may be much less rooted in explicit intentions, internal motivations, or specific reward systems than is commonly believed.' article_number: '7846789' author: - first_name: Ralf full_name: Der, Ralf last_name: Der - first_name: Georg S full_name: Martius, Georg S id: 3A276B68-F248-11E8-B48F-1D18A9856A87 last_name: Martius citation: ama: 'Der R, Martius GS. Dynamical self consistency leads to behavioral development and emergent social interactions in robots. In: IEEE; 2017. doi:10.1109/DEVLRN.2016.7846789' apa: 'Der, R., & Martius, G. S. (2017). Dynamical self consistency leads to behavioral development and emergent social interactions in robots. Presented at the ICDL EpiRob: International Conference on Development and Learning and Epigenetic Robotics , Cergy-Pontoise, France: IEEE. https://doi.org/10.1109/DEVLRN.2016.7846789' chicago: Der, Ralf, and Georg S Martius. “Dynamical Self Consistency Leads to Behavioral Development and Emergent Social Interactions in Robots.” IEEE, 2017. https://doi.org/10.1109/DEVLRN.2016.7846789. ieee: 'R. Der and G. S. Martius, “Dynamical self consistency leads to behavioral development and emergent social interactions in robots,” presented at the ICDL EpiRob: International Conference on Development and Learning and Epigenetic Robotics , Cergy-Pontoise, France, 2017.' ista: 'Der R, Martius GS. 2017. Dynamical self consistency leads to behavioral development and emergent social interactions in robots. ICDL EpiRob: International Conference on Development and Learning and Epigenetic Robotics , 7846789.' mla: Der, Ralf, and Georg S. Martius. Dynamical Self Consistency Leads to Behavioral Development and Emergent Social Interactions in Robots. 7846789, IEEE, 2017, doi:10.1109/DEVLRN.2016.7846789. short: R. Der, G.S. Martius, in:, IEEE, 2017. conference: end_date: 2016-09-22 location: Cergy-Pontoise, France name: 'ICDL EpiRob: International Conference on Development and Learning and Epigenetic Robotics ' start_date: 2016-09-19 date_created: 2018-12-11T11:47:43Z date_published: 2017-02-07T00:00:00Z date_updated: 2021-01-12T08:07:51Z day: '07' department: - _id: ChLa - _id: GaTk doi: 10.1109/DEVLRN.2016.7846789 language: - iso: eng month: '02' oa_version: None publication_identifier: isbn: - 978-150905069-7 publication_status: published publisher: IEEE publist_id: '7100' quality_controlled: '1' scopus_import: 1 status: public title: Dynamical self consistency leads to behavioral development and emergent social interactions in robots type: conference user_id: 3E5EF7F0-F248-11E8-B48F-1D18A9856A87 year: '2017' ... --- _id: '658' abstract: - lang: eng text: 'With the accelerated development of robot technologies, control becomes one of the central themes of research. In traditional approaches, the controller, by its internal functionality, finds appropriate actions on the basis of specific objectives for the task at hand. While very successful in many applications, self-organized control schemes seem to be favored in large complex systems with unknown dynamics or which are difficult to model. Reasons are the expected scalability, robustness, and resilience of self-organizing systems. The paper presents a self-learning neurocontroller based on extrinsic differential plasticity introduced recently, applying it to an anthropomorphic musculoskeletal robot arm with attached objects of unknown physical dynamics. The central finding of the paper is the following effect: by the mere feedback through the internal dynamics of the object, the robot is learning to relate each of the objects with a very specific sensorimotor pattern. Specifically, an attached pendulum pilots the arm into a circular motion, a half-filled bottle produces axis oriented shaking behavior, a wheel is getting rotated, and wiping patterns emerge automatically in a table-plus-brush setting. By these object-specific dynamical patterns, the robot may be said to recognize the object''s identity, or in other words, it discovers dynamical affordances of objects. Furthermore, when including hand coordinates obtained from a camera, a dedicated hand-eye coordination self-organizes spontaneously. These phenomena are discussed from a specific dynamical system perspective. Central is the dedicated working regime at the border to instability with its potentially infinite reservoir of (limit cycle) attractors "waiting" to be excited. Besides converging toward one of these attractors, variate behavior is also arising from a self-induced attractor morphing driven by the learning rule. We claim that experimental investigations with this anthropomorphic, self-learning robot not only generate interesting and potentially useful behaviors, but may also help to better understand what subjective human muscle feelings are, how they can be rooted in sensorimotor patterns, and how these concepts may feed back on robotics.' article_number: '00008' article_processing_charge: Yes author: - first_name: Ralf full_name: Der, Ralf last_name: Der - first_name: Georg S full_name: Martius, Georg S id: 3A276B68-F248-11E8-B48F-1D18A9856A87 last_name: Martius citation: ama: Der R, Martius GS. Self organized behavior generation for musculoskeletal robots. Frontiers in Neurorobotics. 2017;11(MAR). doi:10.3389/fnbot.2017.00008 apa: Der, R., & Martius, G. S. (2017). Self organized behavior generation for musculoskeletal robots. Frontiers in Neurorobotics. Frontiers Research Foundation. https://doi.org/10.3389/fnbot.2017.00008 chicago: Der, Ralf, and Georg S Martius. “Self Organized Behavior Generation for Musculoskeletal Robots.” Frontiers in Neurorobotics. Frontiers Research Foundation, 2017. https://doi.org/10.3389/fnbot.2017.00008. ieee: R. Der and G. S. Martius, “Self organized behavior generation for musculoskeletal robots,” Frontiers in Neurorobotics, vol. 11, no. MAR. Frontiers Research Foundation, 2017. ista: Der R, Martius GS. 2017. Self organized behavior generation for musculoskeletal robots. Frontiers in Neurorobotics. 11(MAR), 00008. mla: Der, Ralf, and Georg S. Martius. “Self Organized Behavior Generation for Musculoskeletal Robots.” Frontiers in Neurorobotics, vol. 11, no. MAR, 00008, Frontiers Research Foundation, 2017, doi:10.3389/fnbot.2017.00008. short: R. Der, G.S. Martius, Frontiers in Neurorobotics 11 (2017). date_created: 2018-12-11T11:47:45Z date_published: 2017-03-16T00:00:00Z date_updated: 2021-01-12T08:08:04Z day: '16' ddc: - '006' department: - _id: ChLa - _id: GaTk doi: 10.3389/fnbot.2017.00008 ec_funded: 1 file: - access_level: open_access checksum: b1bc43f96d1df3313c03032c2a46388d content_type: application/pdf creator: system date_created: 2018-12-12T10:18:49Z date_updated: 2020-07-14T12:47:33Z file_id: '5371' file_name: IST-2017-903-v1+1_fnbot-11-00008.pdf file_size: 8439566 relation: main_file file_date_updated: 2020-07-14T12:47:33Z has_accepted_license: '1' intvolume: ' 11' issue: MAR language: - iso: eng month: '03' oa: 1 oa_version: Published Version project: - _id: 25681D80-B435-11E9-9278-68D0E5697425 call_identifier: FP7 grant_number: '291734' name: International IST Postdoc Fellowship Programme publication: Frontiers in Neurorobotics publication_identifier: issn: - '16625218' publication_status: published publisher: Frontiers Research Foundation publist_id: '7078' pubrep_id: '903' quality_controlled: '1' scopus_import: 1 status: public title: Self organized behavior generation for musculoskeletal robots tmp: image: /images/cc_by.png legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0) short: CC BY (4.0) type: journal_article user_id: 2EBD1598-F248-11E8-B48F-1D18A9856A87 volume: 11 year: '2017' ... --- _id: '720' abstract: - lang: eng text: 'Advances in multi-unit recordings pave the way for statistical modeling of activity patterns in large neural populations. Recent studies have shown that the summed activity of all neurons strongly shapes the population response. A separate recent finding has been that neural populations also exhibit criticality, an anomalously large dynamic range for the probabilities of different population activity patterns. Motivated by these two observations, we introduce a class of probabilistic models which takes into account the prior knowledge that the neural population could be globally coupled and close to critical. These models consist of an energy function which parametrizes interactions between small groups of neurons, and an arbitrary positive, strictly increasing, and twice differentiable function which maps the energy of a population pattern to its probability. We show that: 1) augmenting a pairwise Ising model with a nonlinearity yields an accurate description of the activity of retinal ganglion cells which outperforms previous models based on the summed activity of neurons; 2) prior knowledge that the population is critical translates to prior expectations about the shape of the nonlinearity; 3) the nonlinearity admits an interpretation in terms of a continuous latent variable globally coupling the system whose distribution we can infer from data. Our method is independent of the underlying system’s state space; hence, it can be applied to other systems such as natural scenes or amino acid sequences of proteins which are also known to exhibit criticality.' article_number: e1005763 article_processing_charge: Yes author: - first_name: Jan full_name: Humplik, Jan id: 2E9627A8-F248-11E8-B48F-1D18A9856A87 last_name: Humplik - first_name: Gasper full_name: Tkacik, Gasper id: 3D494DCA-F248-11E8-B48F-1D18A9856A87 last_name: Tkacik orcid: 0000-0002-6699-1455 citation: ama: Humplik J, Tkačik G. Probabilistic models for neural populations that naturally capture global coupling and criticality. PLoS Computational Biology. 2017;13(9). doi:10.1371/journal.pcbi.1005763 apa: Humplik, J., & Tkačik, G. (2017). Probabilistic models for neural populations that naturally capture global coupling and criticality. PLoS Computational Biology. Public Library of Science. https://doi.org/10.1371/journal.pcbi.1005763 chicago: Humplik, Jan, and Gašper Tkačik. “Probabilistic Models for Neural Populations That Naturally Capture Global Coupling and Criticality.” PLoS Computational Biology. Public Library of Science, 2017. https://doi.org/10.1371/journal.pcbi.1005763. ieee: J. Humplik and G. Tkačik, “Probabilistic models for neural populations that naturally capture global coupling and criticality,” PLoS Computational Biology, vol. 13, no. 9. Public Library of Science, 2017. ista: Humplik J, Tkačik G. 2017. Probabilistic models for neural populations that naturally capture global coupling and criticality. PLoS Computational Biology. 13(9), e1005763. mla: Humplik, Jan, and Gašper Tkačik. “Probabilistic Models for Neural Populations That Naturally Capture Global Coupling and Criticality.” PLoS Computational Biology, vol. 13, no. 9, e1005763, Public Library of Science, 2017, doi:10.1371/journal.pcbi.1005763. short: J. Humplik, G. Tkačik, PLoS Computational Biology 13 (2017). date_created: 2018-12-11T11:48:08Z date_published: 2017-09-19T00:00:00Z date_updated: 2021-01-12T08:12:21Z day: '19' ddc: - '530' - '571' department: - _id: GaTk doi: 10.1371/journal.pcbi.1005763 file: - access_level: open_access checksum: 81107096c19771c36ddbe6f0282a3acb content_type: application/pdf creator: system date_created: 2018-12-12T10:18:30Z date_updated: 2020-07-14T12:47:53Z file_id: '5352' file_name: IST-2017-884-v1+1_journal.pcbi.1005763.pdf file_size: 14167050 relation: main_file file_date_updated: 2020-07-14T12:47:53Z has_accepted_license: '1' intvolume: ' 13' issue: '9' language: - iso: eng month: '09' oa: 1 oa_version: Published Version project: - _id: 255008E4-B435-11E9-9278-68D0E5697425 grant_number: RGP0065/2012 name: Information processing and computation in fish groups - _id: 254D1A94-B435-11E9-9278-68D0E5697425 call_identifier: FWF grant_number: P 25651-N26 name: Sensitivity to higher-order statistics in natural scenes publication: PLoS Computational Biology publication_identifier: issn: - 1553734X publication_status: published publisher: Public Library of Science publist_id: '6960' pubrep_id: '884' quality_controlled: '1' scopus_import: 1 status: public title: Probabilistic models for neural populations that naturally capture global coupling and criticality tmp: image: /images/cc_by.png legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0) short: CC BY (4.0) type: journal_article user_id: 3E5EF7F0-F248-11E8-B48F-1D18A9856A87 volume: 13 year: '2017' ... --- _id: '725' abstract: - lang: eng text: Individual computations and social interactions underlying collective behavior in groups of animals are of great ethological, behavioral, and theoretical interest. While complex individual behaviors have successfully been parsed into small dictionaries of stereotyped behavioral modes, studies of collective behavior largely ignored these findings; instead, their focus was on inferring single, mode-independent social interaction rules that reproduced macroscopic and often qualitative features of group behavior. Here, we bring these two approaches together to predict individual swimming patterns of adult zebrafish in a group. We show that fish alternate between an “active” mode, in which they are sensitive to the swimming patterns of conspecifics, and a “passive” mode, where they ignore them. Using a model that accounts for these two modes explicitly, we predict behaviors of individual fish with high accuracy, outperforming previous approaches that assumed a single continuous computation by individuals and simple metric or topological weighing of neighbors’ behavior. At the group level, switching between active and passive modes is uncorrelated among fish, but correlated directional swimming behavior still emerges. Our quantitative approach for studying complex, multi-modal individual behavior jointly with emergent group behavior is readily extensible to additional behavioral modes and their neural correlates as well as to other species. author: - first_name: Roy full_name: Harpaz, Roy last_name: Harpaz - first_name: Gasper full_name: Tkacik, Gasper id: 3D494DCA-F248-11E8-B48F-1D18A9856A87 last_name: Tkacik orcid: 0000-0002-6699-1455 - first_name: Elad full_name: Schneidman, Elad last_name: Schneidman citation: ama: Harpaz R, Tkačik G, Schneidman E. Discrete modes of social information processing predict individual behavior of fish in a group. PNAS. 2017;114(38):10149-10154. doi:10.1073/pnas.1703817114 apa: Harpaz, R., Tkačik, G., & Schneidman, E. (2017). Discrete modes of social information processing predict individual behavior of fish in a group. PNAS. National Academy of Sciences. https://doi.org/10.1073/pnas.1703817114 chicago: Harpaz, Roy, Gašper Tkačik, and Elad Schneidman. “Discrete Modes of Social Information Processing Predict Individual Behavior of Fish in a Group.” PNAS. National Academy of Sciences, 2017. https://doi.org/10.1073/pnas.1703817114. ieee: R. Harpaz, G. Tkačik, and E. Schneidman, “Discrete modes of social information processing predict individual behavior of fish in a group,” PNAS, vol. 114, no. 38. National Academy of Sciences, pp. 10149–10154, 2017. ista: Harpaz R, Tkačik G, Schneidman E. 2017. Discrete modes of social information processing predict individual behavior of fish in a group. PNAS. 114(38), 10149–10154. mla: Harpaz, Roy, et al. “Discrete Modes of Social Information Processing Predict Individual Behavior of Fish in a Group.” PNAS, vol. 114, no. 38, National Academy of Sciences, 2017, pp. 10149–54, doi:10.1073/pnas.1703817114. short: R. Harpaz, G. Tkačik, E. Schneidman, PNAS 114 (2017) 10149–10154. date_created: 2018-12-11T11:48:10Z date_published: 2017-09-19T00:00:00Z date_updated: 2021-01-12T08:12:36Z day: '19' department: - _id: GaTk doi: 10.1073/pnas.1703817114 external_id: pmid: - '28874581' intvolume: ' 114' issue: '38' language: - iso: eng main_file_link: - open_access: '1' url: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5617265/ month: '09' oa: 1 oa_version: Submitted Version page: 10149 - 10154 pmid: 1 publication: PNAS publication_identifier: issn: - '00278424' publication_status: published publisher: National Academy of Sciences publist_id: '6953' quality_controlled: '1' scopus_import: 1 status: public title: Discrete modes of social information processing predict individual behavior of fish in a group type: journal_article user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87 volume: 114 year: '2017' ... --- _id: '9709' abstract: - lang: eng text: Across the nervous system, certain population spiking patterns are observed far more frequently than others. A hypothesis about this structure is that these collective activity patterns function as population codewords–collective modes–carrying information distinct from that of any single cell. We investigate this phenomenon in recordings of ∼150 retinal ganglion cells, the retina’s output. We develop a novel statistical model that decomposes the population response into modes; it predicts the distribution of spiking activity in the ganglion cell population with high accuracy. We found that the modes represent localized features of the visual stimulus that are distinct from the features represented by single neurons. Modes form clusters of activity states that are readily discriminated from one another. When we repeated the same visual stimulus, we found that the same mode was robustly elicited. These results suggest that retinal ganglion cells’ collective signaling is endowed with a form of error-correcting code–a principle that may hold in brain areas beyond retina. article_processing_charge: No author: - first_name: Jason full_name: Prentice, Jason last_name: Prentice - first_name: Olivier full_name: Marre, Olivier last_name: Marre - first_name: Mark full_name: Ioffe, Mark last_name: Ioffe - first_name: Adrianna full_name: Loback, Adrianna last_name: Loback - first_name: Gašper full_name: Tkačik, Gašper id: 3D494DCA-F248-11E8-B48F-1D18A9856A87 last_name: Tkačik orcid: 0000-0002-6699-1455 - first_name: Michael full_name: Berry, Michael last_name: Berry citation: ama: 'Prentice J, Marre O, Ioffe M, Loback A, Tkačik G, Berry M. Data from: Error-robust modes of the retinal population code. 2017. doi:10.5061/dryad.1f1rc' apa: 'Prentice, J., Marre, O., Ioffe, M., Loback, A., Tkačik, G., & Berry, M. (2017). Data from: Error-robust modes of the retinal population code. Dryad. https://doi.org/10.5061/dryad.1f1rc' chicago: 'Prentice, Jason, Olivier Marre, Mark Ioffe, Adrianna Loback, Gašper Tkačik, and Michael Berry. “Data from: Error-Robust Modes of the Retinal Population Code.” Dryad, 2017. https://doi.org/10.5061/dryad.1f1rc.' ieee: 'J. Prentice, O. Marre, M. Ioffe, A. Loback, G. Tkačik, and M. Berry, “Data from: Error-robust modes of the retinal population code.” Dryad, 2017.' ista: 'Prentice J, Marre O, Ioffe M, Loback A, Tkačik G, Berry M. 2017. Data from: Error-robust modes of the retinal population code, Dryad, 10.5061/dryad.1f1rc.' mla: 'Prentice, Jason, et al. Data from: Error-Robust Modes of the Retinal Population Code. Dryad, 2017, doi:10.5061/dryad.1f1rc.' short: J. Prentice, O. Marre, M. Ioffe, A. Loback, G. Tkačik, M. Berry, (2017). date_created: 2021-07-23T11:34:34Z date_published: 2017-10-18T00:00:00Z date_updated: 2023-02-21T16:34:41Z day: '18' department: - _id: GaTk doi: 10.5061/dryad.1f1rc main_file_link: - open_access: '1' url: https://doi.org/10.5061/dryad.1f1rc month: '10' oa: 1 oa_version: Published Version publisher: Dryad related_material: record: - id: '1197' relation: used_in_publication status: public status: public title: 'Data from: Error-robust modes of the retinal population code' type: research_data_reference user_id: 6785fbc1-c503-11eb-8a32-93094b40e1cf year: '2017' ... --- _id: '680' abstract: - lang: eng text: In order to respond reliably to specific features of their environment, sensory neurons need to integrate multiple incoming noisy signals. Crucially, they also need to compete for the interpretation of those signals with other neurons representing similar features. The form that this competition should take depends critically on the noise corrupting these signals. In this study we show that for the type of noise commonly observed in sensory systems, whose variance scales with the mean signal, sensory neurons should selectively divide their input signals by their predictions, suppressing ambiguous cues while amplifying others. Any change in the stimulus context alters which inputs are suppressed, leading to a deep dynamic reshaping of neural receptive fields going far beyond simple surround suppression. Paradoxically, these highly variable receptive fields go alongside and are in fact required for an invariant representation of external sensory features. In addition to offering a normative account of context-dependent changes in sensory responses, perceptual inference in the presence of signal-dependent noise accounts for ubiquitous features of sensory neurons such as divisive normalization, gain control and contrast dependent temporal dynamics. article_number: e1005582 author: - first_name: Matthew J full_name: Chalk, Matthew J id: 2BAAC544-F248-11E8-B48F-1D18A9856A87 last_name: Chalk orcid: 0000-0001-7782-4436 - first_name: Paul full_name: Masset, Paul last_name: Masset - first_name: Boris full_name: Gutkin, Boris last_name: Gutkin - first_name: Sophie full_name: Denève, Sophie last_name: Denève citation: ama: Chalk MJ, Masset P, Gutkin B, Denève S. Sensory noise predicts divisive reshaping of receptive fields. PLoS Computational Biology. 2017;13(6). doi:10.1371/journal.pcbi.1005582 apa: Chalk, M. J., Masset, P., Gutkin, B., & Denève, S. (2017). Sensory noise predicts divisive reshaping of receptive fields. PLoS Computational Biology. Public Library of Science. https://doi.org/10.1371/journal.pcbi.1005582 chicago: Chalk, Matthew J, Paul Masset, Boris Gutkin, and Sophie Denève. “Sensory Noise Predicts Divisive Reshaping of Receptive Fields.” PLoS Computational Biology. Public Library of Science, 2017. https://doi.org/10.1371/journal.pcbi.1005582. ieee: M. J. Chalk, P. Masset, B. Gutkin, and S. Denève, “Sensory noise predicts divisive reshaping of receptive fields,” PLoS Computational Biology, vol. 13, no. 6. Public Library of Science, 2017. ista: Chalk MJ, Masset P, Gutkin B, Denève S. 2017. Sensory noise predicts divisive reshaping of receptive fields. PLoS Computational Biology. 13(6), e1005582. mla: Chalk, Matthew J., et al. “Sensory Noise Predicts Divisive Reshaping of Receptive Fields.” PLoS Computational Biology, vol. 13, no. 6, e1005582, Public Library of Science, 2017, doi:10.1371/journal.pcbi.1005582. short: M.J. Chalk, P. Masset, B. Gutkin, S. Denève, PLoS Computational Biology 13 (2017). date_created: 2018-12-11T11:47:53Z date_published: 2017-06-01T00:00:00Z date_updated: 2023-02-23T14:10:54Z day: '01' ddc: - '571' department: - _id: GaTk doi: 10.1371/journal.pcbi.1005582 file: - access_level: open_access checksum: 796a1026076af6f4405a47d985bc7b68 content_type: application/pdf creator: system date_created: 2018-12-12T10:07:47Z date_updated: 2020-07-14T12:47:40Z file_id: '4645' file_name: IST-2017-898-v1+1_journal.pcbi.1005582.pdf file_size: 14555676 relation: main_file file_date_updated: 2020-07-14T12:47:40Z has_accepted_license: '1' intvolume: ' 13' issue: '6' language: - iso: eng month: '06' oa: 1 oa_version: Published Version publication: PLoS Computational Biology publication_identifier: issn: - 1553734X publication_status: published publisher: Public Library of Science publist_id: '7035' pubrep_id: '898' quality_controlled: '1' related_material: record: - id: '9855' relation: research_data status: public scopus_import: 1 status: public title: Sensory noise predicts divisive reshaping of receptive fields tmp: image: /images/cc_by.png legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0) short: CC BY (4.0) type: journal_article user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87 volume: 13 year: '2017' ... --- _id: '9855' abstract: - lang: eng text: Includes derivation of optimal estimation algorithm, generalisation to non-poisson noise statistics, correlated input noise, and implementation of in a multi-layer neural network. article_processing_charge: No author: - first_name: Matthew J full_name: Chalk, Matthew J id: 2BAAC544-F248-11E8-B48F-1D18A9856A87 last_name: Chalk orcid: 0000-0001-7782-4436 - first_name: Paul full_name: Masset, Paul last_name: Masset - first_name: Boris full_name: Gutkin, Boris last_name: Gutkin - first_name: Sophie full_name: Denève, Sophie last_name: Denève citation: ama: Chalk MJ, Masset P, Gutkin B, Denève S. Supplementary appendix. 2017. doi:10.1371/journal.pcbi.1005582.s001 apa: Chalk, M. J., Masset, P., Gutkin, B., & Denève, S. (2017). Supplementary appendix. Public Library of Science. https://doi.org/10.1371/journal.pcbi.1005582.s001 chicago: Chalk, Matthew J, Paul Masset, Boris Gutkin, and Sophie Denève. “Supplementary Appendix.” Public Library of Science, 2017. https://doi.org/10.1371/journal.pcbi.1005582.s001. ieee: M. J. Chalk, P. Masset, B. Gutkin, and S. Denève, “Supplementary appendix.” Public Library of Science, 2017. ista: Chalk MJ, Masset P, Gutkin B, Denève S. 2017. Supplementary appendix, Public Library of Science, 10.1371/journal.pcbi.1005582.s001. mla: Chalk, Matthew J., et al. Supplementary Appendix. Public Library of Science, 2017, doi:10.1371/journal.pcbi.1005582.s001. short: M.J. Chalk, P. Masset, B. Gutkin, S. Denève, (2017). date_created: 2021-08-10T07:05:10Z date_published: 2017-06-01T00:00:00Z date_updated: 2023-02-23T12:52:17Z day: '01' department: - _id: GaTk doi: 10.1371/journal.pcbi.1005582.s001 month: '06' oa_version: Published Version publisher: Public Library of Science related_material: record: - id: '680' relation: used_in_publication status: public status: public title: Supplementary appendix type: research_data_reference user_id: 6785fbc1-c503-11eb-8a32-93094b40e1cf year: '2017' ... --- _id: '666' abstract: - lang: eng text: Antibiotics elicit drastic changes in microbial gene expression, including the induction of stress response genes. While certain stress responses are known to “cross-protect” bacteria from other stressors, it is unclear whether cellular responses to antibiotics have a similar protective role. By measuring the genome-wide transcriptional response dynamics of Escherichia coli to four antibiotics, we found that trimethoprim induces a rapid acid stress response that protects bacteria from subsequent exposure to acid. Combining microfluidics with time-lapse imaging to monitor survival and acid stress response in single cells revealed that the noisy expression of the acid resistance operon gadBC correlates with single-cell survival. Cells with higher gadBC expression following trimethoprim maintain higher intracellular pH and survive the acid stress longer. The seemingly random single-cell survival under acid stress can therefore be predicted from gadBC expression and rationalized in terms of GadB/C molecular function. Overall, we provide a roadmap for identifying the molecular mechanisms of single-cell cross-protection between antibiotics and other stressors. article_processing_charge: Yes (in subscription journal) author: - first_name: Karin full_name: Mitosch, Karin id: 39B66846-F248-11E8-B48F-1D18A9856A87 last_name: Mitosch - first_name: Georg full_name: Rieckh, Georg id: 34DA8BD6-F248-11E8-B48F-1D18A9856A87 last_name: Rieckh - first_name: Tobias full_name: Bollenbach, Tobias id: 3E6DB97A-F248-11E8-B48F-1D18A9856A87 last_name: Bollenbach orcid: 0000-0003-4398-476X citation: ama: Mitosch K, Rieckh G, Bollenbach MT. Noisy response to antibiotic stress predicts subsequent single cell survival in an acidic environment. Cell Systems. 2017;4(4):393-403. doi:10.1016/j.cels.2017.03.001 apa: Mitosch, K., Rieckh, G., & Bollenbach, M. T. (2017). Noisy response to antibiotic stress predicts subsequent single cell survival in an acidic environment. Cell Systems. Cell Press. https://doi.org/10.1016/j.cels.2017.03.001 chicago: Mitosch, Karin, Georg Rieckh, and Mark Tobias Bollenbach. “Noisy Response to Antibiotic Stress Predicts Subsequent Single Cell Survival in an Acidic Environment.” Cell Systems. Cell Press, 2017. https://doi.org/10.1016/j.cels.2017.03.001. ieee: K. Mitosch, G. Rieckh, and M. T. Bollenbach, “Noisy response to antibiotic stress predicts subsequent single cell survival in an acidic environment,” Cell Systems, vol. 4, no. 4. Cell Press, pp. 393–403, 2017. ista: Mitosch K, Rieckh G, Bollenbach MT. 2017. Noisy response to antibiotic stress predicts subsequent single cell survival in an acidic environment. Cell Systems. 4(4), 393–403. mla: Mitosch, Karin, et al. “Noisy Response to Antibiotic Stress Predicts Subsequent Single Cell Survival in an Acidic Environment.” Cell Systems, vol. 4, no. 4, Cell Press, 2017, pp. 393–403, doi:10.1016/j.cels.2017.03.001. short: K. Mitosch, G. Rieckh, M.T. Bollenbach, Cell Systems 4 (2017) 393–403. date_created: 2018-12-11T11:47:48Z date_published: 2017-04-26T00:00:00Z date_updated: 2023-09-07T12:00:25Z day: '26' ddc: - '576' - '610' department: - _id: ToBo - _id: GaTk doi: 10.1016/j.cels.2017.03.001 ec_funded: 1 file: - access_level: open_access checksum: 04ff20011c3d9a601c514aa999a5fe1a content_type: application/pdf creator: system date_created: 2018-12-12T10:13:54Z date_updated: 2020-07-14T12:47:35Z file_id: '5041' file_name: IST-2017-901-v1+1_1-s2.0-S2405471217300868-main.pdf file_size: 2438660 relation: main_file file_date_updated: 2020-07-14T12:47:35Z has_accepted_license: '1' intvolume: ' 4' issue: '4' language: - iso: eng license: https://creativecommons.org/licenses/by-nc-nd/4.0/ month: '04' oa: 1 oa_version: Published Version page: 393 - 403 project: - _id: 25E83C2C-B435-11E9-9278-68D0E5697425 call_identifier: FP7 grant_number: '303507' name: Optimality principles in responses to antibiotics - _id: 25E9AF9E-B435-11E9-9278-68D0E5697425 call_identifier: FWF grant_number: P27201-B22 name: Revealing the mechanisms underlying drug interactions - _id: 25EB3A80-B435-11E9-9278-68D0E5697425 grant_number: RGP0042/2013 name: Revealing the fundamental limits of cell growth publication: Cell Systems publication_identifier: issn: - '24054712' publication_status: published publisher: Cell Press publist_id: '7061' pubrep_id: '901' quality_controlled: '1' related_material: record: - id: '818' relation: dissertation_contains status: public scopus_import: 1 status: public title: Noisy response to antibiotic stress predicts subsequent single cell survival in an acidic environment tmp: image: /images/cc_by_nc_nd.png legal_code_url: https://creativecommons.org/licenses/by-nc-nd/4.0/legalcode name: Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0) short: CC BY-NC-ND (4.0) type: journal_article user_id: 3E5EF7F0-F248-11E8-B48F-1D18A9856A87 volume: 4 year: '2017' ... --- _id: '2016' abstract: - lang: eng text: The Ising model is one of the simplest and most famous models of interacting systems. It was originally proposed to model ferromagnetic interactions in statistical physics and is now widely used to model spatial processes in many areas such as ecology, sociology, and genetics, usually without testing its goodness-of-fit. Here, we propose an exact goodness-of-fit test for the finite-lattice Ising model. The theory of Markov bases has been developed in algebraic statistics for exact goodness-of-fit testing using a Monte Carlo approach. However, this beautiful theory has fallen short of its promise for applications, because finding a Markov basis is usually computationally intractable. We develop a Monte Carlo method for exact goodness-of-fit testing for the Ising model which avoids computing a Markov basis and also leads to a better connectivity of the Markov chain and hence to a faster convergence. We show how this method can be applied to analyze the spatial organization of receptors on the cell membrane. article_processing_charge: No author: - first_name: Abraham full_name: Martin Del Campo Sanchez, Abraham last_name: Martin Del Campo Sanchez - first_name: Sarah A full_name: Cepeda Humerez, Sarah A id: 3DEE19A4-F248-11E8-B48F-1D18A9856A87 last_name: Cepeda Humerez - first_name: Caroline full_name: Uhler, Caroline id: 49ADD78E-F248-11E8-B48F-1D18A9856A87 last_name: Uhler orcid: 0000-0002-7008-0216 citation: ama: Martin Del Campo Sanchez A, Cepeda Humerez SA, Uhler C. Exact goodness-of-fit testing for the Ising model. Scandinavian Journal of Statistics. 2017;44(2):285-306. doi:10.1111/sjos.12251 apa: Martin Del Campo Sanchez, A., Cepeda Humerez, S. A., & Uhler, C. (2017). Exact goodness-of-fit testing for the Ising model. Scandinavian Journal of Statistics. Wiley-Blackwell. https://doi.org/10.1111/sjos.12251 chicago: Martin Del Campo Sanchez, Abraham, Sarah A Cepeda Humerez, and Caroline Uhler. “Exact Goodness-of-Fit Testing for the Ising Model.” Scandinavian Journal of Statistics. Wiley-Blackwell, 2017. https://doi.org/10.1111/sjos.12251. ieee: A. Martin Del Campo Sanchez, S. A. Cepeda Humerez, and C. Uhler, “Exact goodness-of-fit testing for the Ising model,” Scandinavian Journal of Statistics, vol. 44, no. 2. Wiley-Blackwell, pp. 285–306, 2017. ista: Martin Del Campo Sanchez A, Cepeda Humerez SA, Uhler C. 2017. Exact goodness-of-fit testing for the Ising model. Scandinavian Journal of Statistics. 44(2), 285–306. mla: Martin Del Campo Sanchez, Abraham, et al. “Exact Goodness-of-Fit Testing for the Ising Model.” Scandinavian Journal of Statistics, vol. 44, no. 2, Wiley-Blackwell, 2017, pp. 285–306, doi:10.1111/sjos.12251. short: A. Martin Del Campo Sanchez, S.A. Cepeda Humerez, C. Uhler, Scandinavian Journal of Statistics 44 (2017) 285–306. date_created: 2018-12-11T11:55:13Z date_published: 2017-06-01T00:00:00Z date_updated: 2023-09-19T15:13:27Z day: '01' department: - _id: GaTk doi: 10.1111/sjos.12251 external_id: arxiv: - '1410.1242' isi: - '000400985000001' intvolume: ' 44' isi: 1 issue: '2' language: - iso: eng main_file_link: - open_access: '1' url: http://arxiv.org/abs/1410.1242 month: '06' oa: 1 oa_version: Preprint page: 285 - 306 publication: Scandinavian Journal of Statistics publication_identifier: issn: - '03036898' publication_status: published publisher: Wiley-Blackwell publist_id: '5060' quality_controlled: '1' related_material: record: - id: '6473' relation: part_of_dissertation status: public scopus_import: '1' status: public title: Exact goodness-of-fit testing for the Ising model type: journal_article user_id: c635000d-4b10-11ee-a964-aac5a93f6ac1 volume: 44 year: '2017' ... --- _id: '1104' abstract: - lang: eng text: In the early visual system, cells of the same type perform the same computation in different places of the visual field. How these cells code together a complex visual scene is unclear. A common assumption is that cells of a single-type extract a single-stimulus feature to form a feature map, but this has rarely been observed directly. Using large-scale recordings in the rat retina, we show that a homogeneous population of fast OFF ganglion cells simultaneously encodes two radically different features of a visual scene. Cells close to a moving object code quasilinearly for its position, while distant cells remain largely invariant to the object's position and, instead, respond nonlinearly to changes in the object's speed. We develop a quantitative model that accounts for this effect and identify a disinhibitory circuit that mediates it. Ganglion cells of a single type thus do not code for one, but two features simultaneously. This richer, flexible neural map might also be present in other sensory systems. article_number: '1964' article_processing_charge: No author: - first_name: Stephane full_name: Deny, Stephane last_name: Deny - first_name: Ulisse full_name: Ferrari, Ulisse last_name: Ferrari - first_name: Emilie full_name: Mace, Emilie last_name: Mace - first_name: Pierre full_name: Yger, Pierre last_name: Yger - first_name: Romain full_name: Caplette, Romain last_name: Caplette - first_name: Serge full_name: Picaud, Serge last_name: Picaud - first_name: Gasper full_name: Tkacik, Gasper id: 3D494DCA-F248-11E8-B48F-1D18A9856A87 last_name: Tkacik orcid: 0000-0002-6699-1455 - first_name: Olivier full_name: Marre, Olivier last_name: Marre citation: ama: Deny S, Ferrari U, Mace E, et al. Multiplexed computations in retinal ganglion cells of a single type. Nature Communications. 2017;8(1). doi:10.1038/s41467-017-02159-y apa: Deny, S., Ferrari, U., Mace, E., Yger, P., Caplette, R., Picaud, S., … Marre, O. (2017). Multiplexed computations in retinal ganglion cells of a single type. Nature Communications. Nature Publishing Group. https://doi.org/10.1038/s41467-017-02159-y chicago: Deny, Stephane, Ulisse Ferrari, Emilie Mace, Pierre Yger, Romain Caplette, Serge Picaud, Gašper Tkačik, and Olivier Marre. “Multiplexed Computations in Retinal Ganglion Cells of a Single Type.” Nature Communications. Nature Publishing Group, 2017. https://doi.org/10.1038/s41467-017-02159-y. ieee: S. Deny et al., “Multiplexed computations in retinal ganglion cells of a single type,” Nature Communications, vol. 8, no. 1. Nature Publishing Group, 2017. ista: Deny S, Ferrari U, Mace E, Yger P, Caplette R, Picaud S, Tkačik G, Marre O. 2017. Multiplexed computations in retinal ganglion cells of a single type. Nature Communications. 8(1), 1964. mla: Deny, Stephane, et al. “Multiplexed Computations in Retinal Ganglion Cells of a Single Type.” Nature Communications, vol. 8, no. 1, 1964, Nature Publishing Group, 2017, doi:10.1038/s41467-017-02159-y. short: S. Deny, U. Ferrari, E. Mace, P. Yger, R. Caplette, S. Picaud, G. Tkačik, O. Marre, Nature Communications 8 (2017). date_created: 2018-12-11T11:50:10Z date_published: 2017-12-06T00:00:00Z date_updated: 2023-09-20T11:41:19Z day: '06' ddc: - '571' department: - _id: GaTk doi: 10.1038/s41467-017-02159-y ec_funded: 1 external_id: isi: - '000417241200004' file: - access_level: open_access content_type: application/pdf creator: system date_created: 2018-12-12T10:16:06Z date_updated: 2018-12-12T10:16:06Z file_id: '5191' file_name: IST-2018-921-v1+1_s41467-017-02159-y.pdf file_size: 2872887 relation: main_file file_date_updated: 2018-12-12T10:16:06Z has_accepted_license: '1' intvolume: ' 8' isi: 1 issue: '1' language: - iso: eng month: '12' oa: 1 oa_version: Published Version project: - _id: 25CD3DD2-B435-11E9-9278-68D0E5697425 call_identifier: FP7 grant_number: '604102' name: Localization of ion channels and receptors by two and three-dimensional immunoelectron microscopic approaches - _id: 254D1A94-B435-11E9-9278-68D0E5697425 call_identifier: FWF grant_number: P 25651-N26 name: Sensitivity to higher-order statistics in natural scenes publication: Nature Communications publication_identifier: issn: - '20411723' publication_status: published publisher: Nature Publishing Group publist_id: '6266' pubrep_id: '921' quality_controlled: '1' scopus_import: '1' status: public title: Multiplexed computations in retinal ganglion cells of a single type tmp: image: /images/cc_by.png legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0) short: CC BY (4.0) type: journal_article user_id: c635000d-4b10-11ee-a964-aac5a93f6ac1 volume: 8 year: '2017' ... --- _id: '993' abstract: - lang: eng text: In real-world applications, observations are often constrained to a small fraction of a system. Such spatial subsampling can be caused by the inaccessibility or the sheer size of the system, and cannot be overcome by longer sampling. Spatial subsampling can strongly bias inferences about a system’s aggregated properties. To overcome the bias, we derive analytically a subsampling scaling framework that is applicable to different observables, including distributions of neuronal avalanches, of number of people infected during an epidemic outbreak, and of node degrees. We demonstrate how to infer the correct distributions of the underlying full system, how to apply it to distinguish critical from subcritical systems, and how to disentangle subsampling and finite size effects. Lastly, we apply subsampling scaling to neuronal avalanche models and to recordings from developing neural networks. We show that only mature, but not young networks follow power-law scaling, indicating self-organization to criticality during development. article_number: '15140' article_processing_charge: Yes (in subscription journal) author: - first_name: Anna full_name: Levina (Martius), Anna id: 35AF8020-F248-11E8-B48F-1D18A9856A87 last_name: Levina (Martius) - first_name: Viola full_name: Priesemann, Viola last_name: Priesemann citation: ama: Levina (Martius) A, Priesemann V. Subsampling scaling. Nature Communications. 2017;8. doi:10.1038/ncomms15140 apa: Levina (Martius), A., & Priesemann, V. (2017). Subsampling scaling. Nature Communications. Nature Publishing Group. https://doi.org/10.1038/ncomms15140 chicago: Levina (Martius), Anna, and Viola Priesemann. “Subsampling Scaling.” Nature Communications. Nature Publishing Group, 2017. https://doi.org/10.1038/ncomms15140. ieee: A. Levina (Martius) and V. Priesemann, “Subsampling scaling,” Nature Communications, vol. 8. Nature Publishing Group, 2017. ista: Levina (Martius) A, Priesemann V. 2017. Subsampling scaling. Nature Communications. 8, 15140. mla: Levina (Martius), Anna, and Viola Priesemann. “Subsampling Scaling.” Nature Communications, vol. 8, 15140, Nature Publishing Group, 2017, doi:10.1038/ncomms15140. short: A. Levina (Martius), V. Priesemann, Nature Communications 8 (2017). date_created: 2018-12-11T11:49:35Z date_published: 2017-05-04T00:00:00Z date_updated: 2023-09-22T09:54:07Z day: '04' ddc: - '005' - '571' department: - _id: GaTk - _id: JoCs doi: 10.1038/ncomms15140 ec_funded: 1 external_id: isi: - '000400560700001' file: - access_level: open_access checksum: 9880212f8c4c53404c7c6fbf9023c53a content_type: application/pdf creator: system date_created: 2018-12-12T10:15:05Z date_updated: 2020-07-14T12:48:19Z file_id: '5122' file_name: IST-2017-819-v1+1_2017_Levina_SubsamplingScaling.pdf file_size: 746224 relation: main_file file_date_updated: 2020-07-14T12:48:19Z has_accepted_license: '1' intvolume: ' 8' isi: 1 language: - iso: eng month: '05' oa: 1 oa_version: Published Version project: - _id: 25681D80-B435-11E9-9278-68D0E5697425 call_identifier: FP7 grant_number: '291734' name: International IST Postdoc Fellowship Programme publication: Nature Communications publication_identifier: issn: - '20411723' publication_status: published publisher: Nature Publishing Group publist_id: '6406' pubrep_id: '819' quality_controlled: '1' scopus_import: '1' status: public title: Subsampling scaling tmp: image: /images/cc_by.png legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0) short: CC BY (4.0) type: journal_article user_id: c635000d-4b10-11ee-a964-aac5a93f6ac1 volume: 8 year: '2017' ... --- _id: '955' abstract: - lang: eng text: 'Gene expression is controlled by networks of regulatory proteins that interact specifically with external signals and DNA regulatory sequences. These interactions force the network components to co-evolve so as to continually maintain function. Yet, existing models of evolution mostly focus on isolated genetic elements. In contrast, we study the essential process by which regulatory networks grow: the duplication and subsequent specialization of network components. We synthesize a biophysical model of molecular interactions with the evolutionary framework to find the conditions and pathways by which new regulatory functions emerge. We show that specialization of new network components is usually slow, but can be drastically accelerated in the presence of regulatory crosstalk and mutations that promote promiscuous interactions between network components.' article_number: '216' article_processing_charge: Yes (in subscription journal) author: - first_name: Tamar full_name: Friedlander, Tamar id: 36A5845C-F248-11E8-B48F-1D18A9856A87 last_name: Friedlander - first_name: Roshan full_name: Prizak, Roshan id: 4456104E-F248-11E8-B48F-1D18A9856A87 last_name: Prizak - first_name: Nicholas H full_name: Barton, Nicholas H id: 4880FE40-F248-11E8-B48F-1D18A9856A87 last_name: Barton orcid: 0000-0002-8548-5240 - first_name: Gasper full_name: Tkacik, Gasper id: 3D494DCA-F248-11E8-B48F-1D18A9856A87 last_name: Tkacik orcid: 0000-0002-6699-1455 citation: ama: Friedlander T, Prizak R, Barton NH, Tkačik G. Evolution of new regulatory functions on biophysically realistic fitness landscapes. Nature Communications. 2017;8(1). doi:10.1038/s41467-017-00238-8 apa: Friedlander, T., Prizak, R., Barton, N. H., & Tkačik, G. (2017). Evolution of new regulatory functions on biophysically realistic fitness landscapes. Nature Communications. Nature Publishing Group. https://doi.org/10.1038/s41467-017-00238-8 chicago: Friedlander, Tamar, Roshan Prizak, Nicholas H Barton, and Gašper Tkačik. “Evolution of New Regulatory Functions on Biophysically Realistic Fitness Landscapes.” Nature Communications. Nature Publishing Group, 2017. https://doi.org/10.1038/s41467-017-00238-8. ieee: T. Friedlander, R. Prizak, N. H. Barton, and G. Tkačik, “Evolution of new regulatory functions on biophysically realistic fitness landscapes,” Nature Communications, vol. 8, no. 1. Nature Publishing Group, 2017. ista: Friedlander T, Prizak R, Barton NH, Tkačik G. 2017. Evolution of new regulatory functions on biophysically realistic fitness landscapes. Nature Communications. 8(1), 216. mla: Friedlander, Tamar, et al. “Evolution of New Regulatory Functions on Biophysically Realistic Fitness Landscapes.” Nature Communications, vol. 8, no. 1, 216, Nature Publishing Group, 2017, doi:10.1038/s41467-017-00238-8. short: T. Friedlander, R. Prizak, N.H. Barton, G. Tkačik, Nature Communications 8 (2017). date_created: 2018-12-11T11:49:23Z date_published: 2017-08-09T00:00:00Z date_updated: 2023-09-22T10:00:49Z day: '09' ddc: - '539' - '576' department: - _id: GaTk - _id: NiBa doi: 10.1038/s41467-017-00238-8 ec_funded: 1 external_id: isi: - '000407198800005' file: - access_level: open_access checksum: 29a1b5db458048d3bd5c67e0e2a56818 content_type: application/pdf creator: system date_created: 2018-12-12T10:14:14Z date_updated: 2020-07-14T12:48:16Z file_id: '5064' file_name: IST-2017-864-v1+1_s41467-017-00238-8.pdf file_size: 998157 relation: main_file - access_level: open_access checksum: 7b78401e52a576cf3e6bbf8d0abadc17 content_type: application/pdf creator: system date_created: 2018-12-12T10:14:15Z date_updated: 2020-07-14T12:48:16Z file_id: '5065' file_name: IST-2017-864-v1+2_41467_2017_238_MOESM1_ESM.pdf file_size: 9715993 relation: main_file file_date_updated: 2020-07-14T12:48:16Z has_accepted_license: '1' intvolume: ' 8' isi: 1 issue: '1' language: - iso: eng month: '08' oa: 1 oa_version: Published Version project: - _id: 25681D80-B435-11E9-9278-68D0E5697425 call_identifier: FP7 grant_number: '291734' name: International IST Postdoc Fellowship Programme - _id: 25B07788-B435-11E9-9278-68D0E5697425 call_identifier: FP7 grant_number: '250152' name: Limits to selection in biology and in evolutionary computation - _id: 254E9036-B435-11E9-9278-68D0E5697425 call_identifier: FWF grant_number: P28844-B27 name: Biophysics of information processing in gene regulation publication: Nature Communications publication_identifier: issn: - '20411723' publication_status: published publisher: Nature Publishing Group publist_id: '6459' pubrep_id: '864' quality_controlled: '1' related_material: record: - id: '6071' relation: dissertation_contains status: public scopus_import: '1' status: public title: Evolution of new regulatory functions on biophysically realistic fitness landscapes tmp: image: /images/cc_by.png legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0) short: CC BY (4.0) type: journal_article user_id: c635000d-4b10-11ee-a964-aac5a93f6ac1 volume: 8 year: '2017' ... --- _id: '959' abstract: - lang: eng text: In this work it is shown that scale-free tails in metabolic flux distributions inferred in stationary models are an artifact due to reactions involved in thermodynamically unfeasible cycles, unbounded by physical constraints and in principle able to perform work without expenditure of free energy. After implementing thermodynamic constraints by removing such loops, metabolic flux distributions scale meaningfully with the physical limiting factors, acquiring in turn a richer multimodal structure potentially leading to symmetry breaking while optimizing for objective functions. article_processing_charge: No author: - first_name: Daniele full_name: De Martino, Daniele id: 3FF5848A-F248-11E8-B48F-1D18A9856A87 last_name: De Martino orcid: 0000-0002-5214-4706 citation: ama: De Martino D. Scales and multimodal flux distributions in stationary metabolic network models via thermodynamics. Physical Review E Statistical Nonlinear and Soft Matter Physics . 2017;95(6):062419. doi:10.1103/PhysRevE.95.062419 apa: De Martino, D. (2017). Scales and multimodal flux distributions in stationary metabolic network models via thermodynamics. Physical Review E Statistical Nonlinear and Soft Matter Physics . American Institute of Physics. https://doi.org/10.1103/PhysRevE.95.062419 chicago: De Martino, Daniele. “Scales and Multimodal Flux Distributions in Stationary Metabolic Network Models via Thermodynamics.” Physical Review E Statistical Nonlinear and Soft Matter Physics . American Institute of Physics, 2017. https://doi.org/10.1103/PhysRevE.95.062419. ieee: D. De Martino, “Scales and multimodal flux distributions in stationary metabolic network models via thermodynamics,” Physical Review E Statistical Nonlinear and Soft Matter Physics , vol. 95, no. 6. American Institute of Physics, p. 062419, 2017. ista: De Martino D. 2017. Scales and multimodal flux distributions in stationary metabolic network models via thermodynamics. Physical Review E Statistical Nonlinear and Soft Matter Physics . 95(6), 062419. mla: De Martino, Daniele. “Scales and Multimodal Flux Distributions in Stationary Metabolic Network Models via Thermodynamics.” Physical Review E Statistical Nonlinear and Soft Matter Physics , vol. 95, no. 6, American Institute of Physics, 2017, p. 062419, doi:10.1103/PhysRevE.95.062419. short: D. De Martino, Physical Review E Statistical Nonlinear and Soft Matter Physics 95 (2017) 062419. date_created: 2018-12-11T11:49:25Z date_published: 2017-06-28T00:00:00Z date_updated: 2023-09-22T09:59:01Z day: '28' department: - _id: GaTk doi: 10.1103/PhysRevE.95.062419 ec_funded: 1 external_id: isi: - '000404546400004' intvolume: ' 95' isi: 1 issue: '6' language: - iso: eng main_file_link: - open_access: '1' url: https://arxiv.org/pdf/1703.00853.pdf month: '06' oa: 1 oa_version: Submitted Version page: '062419' project: - _id: 25681D80-B435-11E9-9278-68D0E5697425 call_identifier: FP7 grant_number: '291734' name: International IST Postdoc Fellowship Programme publication: ' Physical Review E Statistical Nonlinear and Soft Matter Physics ' publication_identifier: issn: - '24700045' publication_status: published publisher: American Institute of Physics publist_id: '6446' quality_controlled: '1' scopus_import: '1' status: public title: Scales and multimodal flux distributions in stationary metabolic network models via thermodynamics type: journal_article user_id: c635000d-4b10-11ee-a964-aac5a93f6ac1 volume: 95 year: '2017' ... --- _id: '947' abstract: - lang: eng text: Viewing the ways a living cell can organize its metabolism as the phase space of a physical system, regulation can be seen as the ability to reduce the entropy of that space by selecting specific cellular configurations that are, in some sense, optimal. Here we quantify the amount of regulation required to control a cell's growth rate by a maximum-entropy approach to the space of underlying metabolic phenotypes, where a configuration corresponds to a metabolic flux pattern as described by genome-scale models. We link the mean growth rate achieved by a population of cells to the minimal amount of metabolic regulation needed to achieve it through a phase diagram that highlights how growth suppression can be as costly (in regulatory terms) as growth enhancement. Moreover, we provide an interpretation of the inverse temperature β controlling maximum-entropy distributions based on the underlying growth dynamics. Specifically, we show that the asymptotic value of β for a cell population can be expected to depend on (i) the carrying capacity of the environment, (ii) the initial size of the colony, and (iii) the probability distribution from which the inoculum was sampled. Results obtained for E. coli and human cells are found to be remarkably consistent with empirical evidence. article_number: '010401' article_processing_charge: No author: - first_name: Daniele full_name: De Martino, Daniele id: 3FF5848A-F248-11E8-B48F-1D18A9856A87 last_name: De Martino orcid: 0000-0002-5214-4706 - first_name: Fabrizio full_name: Capuani, Fabrizio last_name: Capuani - first_name: Andrea full_name: De Martino, Andrea last_name: De Martino citation: ama: De Martino D, Capuani F, De Martino A. Quantifying the entropic cost of cellular growth control. Physical Review E Statistical Nonlinear and Soft Matter Physics . 2017;96(1). doi:10.1103/PhysRevE.96.010401 apa: De Martino, D., Capuani, F., & De Martino, A. (2017). Quantifying the entropic cost of cellular growth control. Physical Review E Statistical Nonlinear and Soft Matter Physics . American Institute of Physics. https://doi.org/10.1103/PhysRevE.96.010401 chicago: De Martino, Daniele, Fabrizio Capuani, and Andrea De Martino. “Quantifying the Entropic Cost of Cellular Growth Control.” Physical Review E Statistical Nonlinear and Soft Matter Physics . American Institute of Physics, 2017. https://doi.org/10.1103/PhysRevE.96.010401. ieee: D. De Martino, F. Capuani, and A. De Martino, “Quantifying the entropic cost of cellular growth control,” Physical Review E Statistical Nonlinear and Soft Matter Physics , vol. 96, no. 1. American Institute of Physics, 2017. ista: De Martino D, Capuani F, De Martino A. 2017. Quantifying the entropic cost of cellular growth control. Physical Review E Statistical Nonlinear and Soft Matter Physics . 96(1), 010401. mla: De Martino, Daniele, et al. “Quantifying the Entropic Cost of Cellular Growth Control.” Physical Review E Statistical Nonlinear and Soft Matter Physics , vol. 96, no. 1, 010401, American Institute of Physics, 2017, doi:10.1103/PhysRevE.96.010401. short: D. De Martino, F. Capuani, A. De Martino, Physical Review E Statistical Nonlinear and Soft Matter Physics 96 (2017). date_created: 2018-12-11T11:49:21Z date_published: 2017-07-10T00:00:00Z date_updated: 2023-09-22T10:03:50Z day: '10' department: - _id: GaTk doi: 10.1103/PhysRevE.96.010401 ec_funded: 1 external_id: isi: - '000405194200002' intvolume: ' 96' isi: 1 issue: '1' language: - iso: eng main_file_link: - open_access: '1' url: https://arxiv.org/abs/1703.00219 month: '07' oa: 1 oa_version: Submitted Version project: - _id: 25681D80-B435-11E9-9278-68D0E5697425 call_identifier: FP7 grant_number: '291734' name: International IST Postdoc Fellowship Programme publication: ' Physical Review E Statistical Nonlinear and Soft Matter Physics ' publication_identifier: issn: - '24700045' publication_status: published publisher: American Institute of Physics publist_id: '6470' quality_controlled: '1' scopus_import: '1' status: public title: Quantifying the entropic cost of cellular growth control type: journal_article user_id: c635000d-4b10-11ee-a964-aac5a93f6ac1 volume: 96 year: '2017' ... --- _id: '943' abstract: - lang: eng text: Like many developing tissues, the vertebrate neural tube is patterned by antiparallel morphogen gradients. To understand how these inputs are interpreted, we measured morphogen signaling and target gene expression in mouse embryos and chick ex vivo assays. From these data, we derived and validated a characteristic decoding map that relates morphogen input to the positional identity of neural progenitors. Analysis of the observed responses indicates that the underlying interpretation strategy minimizes patterning errors in response to the joint input of noisy opposing gradients. We reverse-engineered a transcriptional network that provides a mechanistic basis for the observed cell fate decisions and accounts for the precision and dynamics of pattern formation. Together, our data link opposing gradient dynamics in a growing tissue to precise pattern formation. article_processing_charge: No author: - first_name: Marcin P full_name: Zagórski, Marcin P id: 343DA0DC-F248-11E8-B48F-1D18A9856A87 last_name: Zagórski orcid: 0000-0001-7896-7762 - first_name: Yoji full_name: Tabata, Yoji last_name: Tabata - first_name: Nathalie full_name: Brandenberg, Nathalie last_name: Brandenberg - first_name: Matthias full_name: Lutolf, Matthias last_name: Lutolf - first_name: Gasper full_name: Tkacik, Gasper id: 3D494DCA-F248-11E8-B48F-1D18A9856A87 last_name: Tkacik orcid: 0000-0002-6699-1455 - first_name: Tobias full_name: Bollenbach, Tobias last_name: Bollenbach - first_name: James full_name: Briscoe, James last_name: Briscoe - first_name: Anna full_name: Kicheva, Anna id: 3959A2A0-F248-11E8-B48F-1D18A9856A87 last_name: Kicheva orcid: 0000-0003-4509-4998 citation: ama: Zagórski MP, Tabata Y, Brandenberg N, et al. Decoding of position in the developing neural tube from antiparallel morphogen gradients. Science. 2017;356(6345):1379-1383. doi:10.1126/science.aam5887 apa: Zagórski, M. P., Tabata, Y., Brandenberg, N., Lutolf, M., Tkačik, G., Bollenbach, T., … Kicheva, A. (2017). Decoding of position in the developing neural tube from antiparallel morphogen gradients. Science. American Association for the Advancement of Science. https://doi.org/10.1126/science.aam5887 chicago: Zagórski, Marcin P, Yoji Tabata, Nathalie Brandenberg, Matthias Lutolf, Gašper Tkačik, Tobias Bollenbach, James Briscoe, and Anna Kicheva. “Decoding of Position in the Developing Neural Tube from Antiparallel Morphogen Gradients.” Science. American Association for the Advancement of Science, 2017. https://doi.org/10.1126/science.aam5887. ieee: M. P. Zagórski et al., “Decoding of position in the developing neural tube from antiparallel morphogen gradients,” Science, vol. 356, no. 6345. American Association for the Advancement of Science, pp. 1379–1383, 2017. ista: Zagórski MP, Tabata Y, Brandenberg N, Lutolf M, Tkačik G, Bollenbach T, Briscoe J, Kicheva A. 2017. Decoding of position in the developing neural tube from antiparallel morphogen gradients. Science. 356(6345), 1379–1383. mla: Zagórski, Marcin P., et al. “Decoding of Position in the Developing Neural Tube from Antiparallel Morphogen Gradients.” Science, vol. 356, no. 6345, American Association for the Advancement of Science, 2017, pp. 1379–83, doi:10.1126/science.aam5887. short: M.P. Zagórski, Y. Tabata, N. Brandenberg, M. Lutolf, G. Tkačik, T. Bollenbach, J. Briscoe, A. Kicheva, Science 356 (2017) 1379–1383. date_created: 2018-12-11T11:49:20Z date_published: 2017-06-30T00:00:00Z date_updated: 2023-09-26T15:38:05Z day: '30' department: - _id: AnKi - _id: GaTk doi: 10.1126/science.aam5887 ec_funded: 1 external_id: isi: - '000404351500036' pmid: - '28663499' intvolume: ' 356' isi: 1 issue: '6345' language: - iso: eng main_file_link: - open_access: '1' url: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5568706/ month: '06' oa: 1 oa_version: Submitted Version page: 1379 - 1383 pmid: 1 project: - _id: 254E9036-B435-11E9-9278-68D0E5697425 call_identifier: FWF grant_number: P28844-B27 name: Biophysics of information processing in gene regulation - _id: B6FC0238-B512-11E9-945C-1524E6697425 call_identifier: H2020 grant_number: '680037' name: Coordination of Patterning And Growth In the Spinal Cord - _id: 25681D80-B435-11E9-9278-68D0E5697425 call_identifier: FP7 grant_number: '291734' name: International IST Postdoc Fellowship Programme - _id: 2524F500-B435-11E9-9278-68D0E5697425 call_identifier: FP7 grant_number: '201439' name: Developing High-Throughput Bioassays for Human Cancers in Zebrafish publication: Science publication_identifier: issn: - '00368075' publication_status: published publisher: American Association for the Advancement of Science publist_id: '6474' quality_controlled: '1' scopus_import: '1' status: public title: Decoding of position in the developing neural tube from antiparallel morphogen gradients type: journal_article user_id: c635000d-4b10-11ee-a964-aac5a93f6ac1 volume: 356 year: '2017' ... --- _id: '823' abstract: - lang: eng text: The resolution of a linear system with positive integer variables is a basic yet difficult computational problem with many applications. We consider sparse uncorrelated random systems parametrised by the density c and the ratio α=N/M between number of variables N and number of constraints M. By means of ensemble calculations we show that the space of feasible solutions endows a Van-Der-Waals phase diagram in the plane (c, α). We give numerical evidence that the associated computational problems become more difficult across the critical point and in particular in the coexistence region. article_number: '093404' article_processing_charge: No author: - first_name: Simona full_name: Colabrese, Simona last_name: Colabrese - first_name: Daniele full_name: De Martino, Daniele id: 3FF5848A-F248-11E8-B48F-1D18A9856A87 last_name: De Martino orcid: 0000-0002-5214-4706 - first_name: Luca full_name: Leuzzi, Luca last_name: Leuzzi - first_name: Enzo full_name: Marinari, Enzo last_name: Marinari citation: ama: 'Colabrese S, De Martino D, Leuzzi L, Marinari E. Phase transitions in integer linear problems. Journal of Statistical Mechanics: Theory and Experiment. 2017;2017(9). doi:10.1088/1742-5468/aa85c3' apa: 'Colabrese, S., De Martino, D., Leuzzi, L., & Marinari, E. (2017). Phase transitions in integer linear problems. Journal of Statistical Mechanics: Theory and Experiment. IOPscience. https://doi.org/10.1088/1742-5468/aa85c3' chicago: 'Colabrese, Simona, Daniele De Martino, Luca Leuzzi, and Enzo Marinari. “Phase Transitions in Integer Linear Problems.” Journal of Statistical Mechanics: Theory and Experiment. IOPscience, 2017. https://doi.org/10.1088/1742-5468/aa85c3.' ieee: 'S. Colabrese, D. De Martino, L. Leuzzi, and E. Marinari, “Phase transitions in integer linear problems,” Journal of Statistical Mechanics: Theory and Experiment, vol. 2017, no. 9. IOPscience, 2017.' ista: 'Colabrese S, De Martino D, Leuzzi L, Marinari E. 2017. Phase transitions in integer linear problems. Journal of Statistical Mechanics: Theory and Experiment. 2017(9), 093404.' mla: 'Colabrese, Simona, et al. “Phase Transitions in Integer Linear Problems.” Journal of Statistical Mechanics: Theory and Experiment, vol. 2017, no. 9, 093404, IOPscience, 2017, doi:10.1088/1742-5468/aa85c3.' short: 'S. Colabrese, D. De Martino, L. Leuzzi, E. Marinari, Journal of Statistical Mechanics: Theory and Experiment 2017 (2017).' date_created: 2018-12-11T11:48:41Z date_published: 2017-09-26T00:00:00Z date_updated: 2023-09-26T16:18:12Z day: '26' department: - _id: GaTk doi: 10.1088/1742-5468/aa85c3 ec_funded: 1 external_id: isi: - '000411842900001' intvolume: ' 2017' isi: 1 issue: '9' language: - iso: eng main_file_link: - open_access: '1' url: https://arxiv.org/abs/1705.06303 month: '09' oa: 1 oa_version: Submitted Version project: - _id: 25681D80-B435-11E9-9278-68D0E5697425 call_identifier: FP7 grant_number: '291734' name: International IST Postdoc Fellowship Programme publication: ' Journal of Statistical Mechanics: Theory and Experiment' publication_identifier: issn: - '17425468' publication_status: published publisher: IOPscience publist_id: '6826' quality_controlled: '1' scopus_import: '1' status: public title: Phase transitions in integer linear problems type: journal_article user_id: c635000d-4b10-11ee-a964-aac5a93f6ac1 volume: 2017 year: '2017' ... --- _id: '730' abstract: - lang: eng text: Neural responses are highly structured, with population activity restricted to a small subset of the astronomical range of possible activity patterns. Characterizing these statistical regularities is important for understanding circuit computation, but challenging in practice. Here we review recent approaches based on the maximum entropy principle used for quantifying collective behavior in neural activity. We highlight recent models that capture population-level statistics of neural data, yielding insights into the organization of the neural code and its biological substrate. Furthermore, the MaxEnt framework provides a general recipe for constructing surrogate ensembles that preserve aspects of the data, but are otherwise maximally unstructured. This idea can be used to generate a hierarchy of controls against which rigorous statistical tests are possible. article_processing_charge: No author: - first_name: Cristina full_name: Savin, Cristina id: 3933349E-F248-11E8-B48F-1D18A9856A87 last_name: Savin - first_name: Gasper full_name: Tkacik, Gasper id: 3D494DCA-F248-11E8-B48F-1D18A9856A87 last_name: Tkacik orcid: 0000-0002-6699-1455 citation: ama: Savin C, Tkačik G. Maximum entropy models as a tool for building precise neural controls. Current Opinion in Neurobiology. 2017;46:120-126. doi:10.1016/j.conb.2017.08.001 apa: Savin, C., & Tkačik, G. (2017). Maximum entropy models as a tool for building precise neural controls. Current Opinion in Neurobiology. Elsevier. https://doi.org/10.1016/j.conb.2017.08.001 chicago: Savin, Cristina, and Gašper Tkačik. “Maximum Entropy Models as a Tool for Building Precise Neural Controls.” Current Opinion in Neurobiology. Elsevier, 2017. https://doi.org/10.1016/j.conb.2017.08.001. ieee: C. Savin and G. Tkačik, “Maximum entropy models as a tool for building precise neural controls,” Current Opinion in Neurobiology, vol. 46. Elsevier, pp. 120–126, 2017. ista: Savin C, Tkačik G. 2017. Maximum entropy models as a tool for building precise neural controls. Current Opinion in Neurobiology. 46, 120–126. mla: Savin, Cristina, and Gašper Tkačik. “Maximum Entropy Models as a Tool for Building Precise Neural Controls.” Current Opinion in Neurobiology, vol. 46, Elsevier, 2017, pp. 120–26, doi:10.1016/j.conb.2017.08.001. short: C. Savin, G. Tkačik, Current Opinion in Neurobiology 46 (2017) 120–126. date_created: 2018-12-11T11:48:11Z date_published: 2017-10-01T00:00:00Z date_updated: 2023-09-28T11:32:22Z day: '01' department: - _id: GaTk doi: 10.1016/j.conb.2017.08.001 ec_funded: 1 external_id: isi: - '000416196400016' intvolume: ' 46' isi: 1 language: - iso: eng month: '10' oa_version: None page: 120 - 126 project: - _id: 25681D80-B435-11E9-9278-68D0E5697425 call_identifier: FP7 grant_number: '291734' name: International IST Postdoc Fellowship Programme publication: Current Opinion in Neurobiology publication_identifier: issn: - '09594388' publication_status: published publisher: Elsevier publist_id: '6943' quality_controlled: '1' scopus_import: '1' status: public title: Maximum entropy models as a tool for building precise neural controls type: journal_article user_id: c635000d-4b10-11ee-a964-aac5a93f6ac1 volume: 46 year: '2017' ...