--- _id: '9226' abstract: - lang: eng text: 'Half a century after Lewis Wolpert''s seminal conceptual advance on how cellular fates distribute in space, we provide a brief historical perspective on how the concept of positional information emerged and influenced the field of developmental biology and beyond. We focus on a modern interpretation of this concept in terms of information theory, largely centered on its application to cell specification in the early Drosophila embryo. We argue that a true physical variable (position) is encoded in local concentrations of patterning molecules, that this mapping is stochastic, and that the processes by which positions and corresponding cell fates are determined based on these concentrations need to take such stochasticity into account. With this approach, we shift the focus from biological mechanisms, molecules, genes and pathways to quantitative systems-level questions: where does positional information reside, how it is transformed and accessed during development, and what fundamental limits it is subject to?' acknowledgement: This work was supported in part by the National Science Foundation, through the Center for the Physics of Biological Function (PHY-1734030), by the National Institutes of Health (R01GM097275) and by the Fonds zur Förderung der wissenschaftlichen Forschung (FWF P28844). Deposited in PMC for release after 12 months. article_number: dev176065 article_processing_charge: No article_type: original author: - first_name: Gašper full_name: Tkačik, Gašper id: 3D494DCA-F248-11E8-B48F-1D18A9856A87 last_name: Tkačik orcid: 0000-0002-6699-1455 - first_name: Thomas full_name: Gregor, Thomas last_name: Gregor citation: ama: Tkačik G, Gregor T. The many bits of positional information. Development. 2021;148(2). doi:10.1242/dev.176065 apa: Tkačik, G., & Gregor, T. (2021). The many bits of positional information. Development. The Company of Biologists. https://doi.org/10.1242/dev.176065 chicago: Tkačik, Gašper, and Thomas Gregor. “The Many Bits of Positional Information.” Development. The Company of Biologists, 2021. https://doi.org/10.1242/dev.176065. ieee: G. Tkačik and T. Gregor, “The many bits of positional information,” Development, vol. 148, no. 2. The Company of Biologists, 2021. ista: Tkačik G, Gregor T. 2021. The many bits of positional information. Development. 148(2), dev176065. mla: Tkačik, Gašper, and Thomas Gregor. “The Many Bits of Positional Information.” Development, vol. 148, no. 2, dev176065, The Company of Biologists, 2021, doi:10.1242/dev.176065. short: G. Tkačik, T. Gregor, Development 148 (2021). date_created: 2021-03-07T23:01:25Z date_published: 2021-02-01T00:00:00Z date_updated: 2023-08-07T13:57:30Z day: '01' department: - _id: GaTk doi: 10.1242/dev.176065 external_id: isi: - '000613906000007' pmid: - '33526425' intvolume: ' 148' isi: 1 issue: '2' language: - iso: eng main_file_link: - open_access: '1' url: https://doi.org/10.1242/dev.176065 month: '02' oa: 1 oa_version: Published Version 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: Development publication_identifier: eissn: - 1477-9129 publication_status: published publisher: The Company of Biologists quality_controlled: '1' scopus_import: '1' status: public title: The many bits of positional information type: journal_article user_id: 4359f0d1-fa6c-11eb-b949-802e58b17ae8 volume: 148 year: '2021' ... --- _id: '9439' abstract: - lang: eng text: The ability to adapt to changes in stimulus statistics is a hallmark of sensory systems. Here, we developed a theoretical framework that can account for the dynamics of adaptation from an information processing perspective. We use this framework to optimize and analyze adaptive sensory codes, and we show that codes optimized for stationary environments can suffer from prolonged periods of poor performance when the environment changes. To mitigate the adversarial effects of these environmental changes, sensory systems must navigate tradeoffs between the ability to accurately encode incoming stimuli and the ability to rapidly detect and adapt to changes in the distribution of these stimuli. We derive families of codes that balance these objectives, and we demonstrate their close match to experimentally observed neural dynamics during mean and variance adaptation. Our results provide a unifying perspective on adaptation across a range of sensory systems, environments, and sensory tasks. acknowledgement: We thank D. Kastner and T. Münch for generously providing figures from their work. We also thank V. Jayaraman, M. Noorman, T. Ma, and K. Krishnamurthy for useful discussions and feedback on the manuscript. W.F.M. was funded by the European Union’s Horizon 2020 Research and Innovation Programme under Marie Skłodowska-Curie Grant Agreement No. 754411. A.M.H. was supported by the Howard Hughes Medical Institute. article_processing_charge: No article_type: original author: - first_name: Wiktor F full_name: Mlynarski, Wiktor F id: 358A453A-F248-11E8-B48F-1D18A9856A87 last_name: Mlynarski - first_name: Ann M. full_name: Hermundstad, Ann M. last_name: Hermundstad citation: ama: Mlynarski WF, Hermundstad AM. Efficient and adaptive sensory codes. Nature Neuroscience. 2021;24:998-1009. doi:10.1038/s41593-021-00846-0 apa: Mlynarski, W. F., & Hermundstad, A. M. (2021). Efficient and adaptive sensory codes. Nature Neuroscience. Springer Nature. https://doi.org/10.1038/s41593-021-00846-0 chicago: Mlynarski, Wiktor F, and Ann M. Hermundstad. “Efficient and Adaptive Sensory Codes.” Nature Neuroscience. Springer Nature, 2021. https://doi.org/10.1038/s41593-021-00846-0. ieee: W. F. Mlynarski and A. M. Hermundstad, “Efficient and adaptive sensory codes,” Nature Neuroscience, vol. 24. Springer Nature, pp. 998–1009, 2021. ista: Mlynarski WF, Hermundstad AM. 2021. Efficient and adaptive sensory codes. Nature Neuroscience. 24, 998–1009. mla: Mlynarski, Wiktor F., and Ann M. Hermundstad. “Efficient and Adaptive Sensory Codes.” Nature Neuroscience, vol. 24, Springer Nature, 2021, pp. 998–1009, doi:10.1038/s41593-021-00846-0. short: W.F. Mlynarski, A.M. Hermundstad, Nature Neuroscience 24 (2021) 998–1009. date_created: 2021-05-30T22:01:24Z date_published: 2021-05-20T00:00:00Z date_updated: 2023-08-08T13:51:14Z day: '20' department: - _id: GaTk doi: 10.1038/s41593-021-00846-0 ec_funded: 1 external_id: isi: - '000652577300003' intvolume: ' 24' isi: 1 language: - iso: eng main_file_link: - open_access: '1' url: 'https://doi.org/10.1101/669200 ' month: '05' oa: 1 oa_version: Preprint page: 998-1009 project: - _id: 260C2330-B435-11E9-9278-68D0E5697425 call_identifier: H2020 grant_number: '754411' name: ISTplus - Postdoctoral Fellowships publication: Nature Neuroscience publication_identifier: eissn: - 1546-1726 issn: - 1097-6256 publication_status: published publisher: Springer Nature quality_controlled: '1' scopus_import: '1' status: public title: Efficient and adaptive sensory codes type: journal_article user_id: 4359f0d1-fa6c-11eb-b949-802e58b17ae8 volume: 24 year: '2021' ... --- _id: '9822' abstract: - lang: eng text: Attachment of adhesive molecules on cell culture surfaces to restrict cell adhesion to defined areas and shapes has been vital for the progress of in vitro research. In currently existing patterning methods, a combination of pattern properties such as stability, precision, specificity, high-throughput outcome, and spatiotemporal control is highly desirable but challenging to achieve. Here, we introduce a versatile and high-throughput covalent photoimmobilization technique, comprising a light-dose-dependent patterning step and a subsequent functionalization of the pattern via click chemistry. This two-step process is feasible on arbitrary surfaces and allows for generation of sustainable patterns and gradients. The method is validated in different biological systems by patterning adhesive ligands on cell-repellent surfaces, thereby constraining the growth and migration of cells to the designated areas. We then implement a sequential photopatterning approach by adding a second switchable patterning step, allowing for spatiotemporal control over two distinct surface patterns. As a proof of concept, we reconstruct the dynamics of the tip/stalk cell switch during angiogenesis. Our results show that the spatiotemporal control provided by our “sequential photopatterning” system is essential for mimicking dynamic biological processes and that our innovative approach has great potential for further applications in cell science. acknowledgement: We would like to thank Charlott Leu for the production of our chromium wafers, Louise Ritter for her contribution of the IF stainings in Figure 4, Shokoufeh Teymouri for her help with the Bioinert coated slides, and finally Prof. Dr. Joachim Rädler for his valuable scientific guidance. article_processing_charge: Yes (in subscription journal) article_type: original author: - first_name: Themistoklis full_name: Zisis, Themistoklis last_name: Zisis - first_name: Jan full_name: Schwarz, Jan id: 346C1EC6-F248-11E8-B48F-1D18A9856A87 last_name: Schwarz - first_name: Miriam full_name: Balles, Miriam last_name: Balles - first_name: Maibritt full_name: Kretschmer, Maibritt last_name: Kretschmer - first_name: Maria full_name: Nemethova, Maria id: 34E27F1C-F248-11E8-B48F-1D18A9856A87 last_name: Nemethova - 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: Robert full_name: Hauschild, Robert id: 4E01D6B4-F248-11E8-B48F-1D18A9856A87 last_name: Hauschild orcid: 0000-0001-9843-3522 - first_name: Janina full_name: Lange, Janina last_name: Lange - 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: Michael K full_name: Sixt, Michael K id: 41E9FBEA-F248-11E8-B48F-1D18A9856A87 last_name: Sixt orcid: 0000-0002-4561-241X - first_name: Stefan full_name: Zahler, Stefan last_name: Zahler citation: ama: Zisis T, Schwarz J, Balles M, et al. Sequential and switchable patterning for studying cellular processes under spatiotemporal control. ACS Applied Materials and Interfaces. 2021;13(30):35545–35560. doi:10.1021/acsami.1c09850 apa: Zisis, T., Schwarz, J., Balles, M., Kretschmer, M., Nemethova, M., Chait, R. P., … Zahler, S. (2021). Sequential and switchable patterning for studying cellular processes under spatiotemporal control. ACS Applied Materials and Interfaces. American Chemical Society. https://doi.org/10.1021/acsami.1c09850 chicago: Zisis, Themistoklis, Jan Schwarz, Miriam Balles, Maibritt Kretschmer, Maria Nemethova, Remy P Chait, Robert Hauschild, et al. “Sequential and Switchable Patterning for Studying Cellular Processes under Spatiotemporal Control.” ACS Applied Materials and Interfaces. American Chemical Society, 2021. https://doi.org/10.1021/acsami.1c09850. ieee: T. Zisis et al., “Sequential and switchable patterning for studying cellular processes under spatiotemporal control,” ACS Applied Materials and Interfaces, vol. 13, no. 30. American Chemical Society, pp. 35545–35560, 2021. ista: Zisis T, Schwarz J, Balles M, Kretschmer M, Nemethova M, Chait RP, Hauschild R, Lange J, Guet CC, Sixt MK, Zahler S. 2021. Sequential and switchable patterning for studying cellular processes under spatiotemporal control. ACS Applied Materials and Interfaces. 13(30), 35545–35560. mla: Zisis, Themistoklis, et al. “Sequential and Switchable Patterning for Studying Cellular Processes under Spatiotemporal Control.” ACS Applied Materials and Interfaces, vol. 13, no. 30, American Chemical Society, 2021, pp. 35545–35560, doi:10.1021/acsami.1c09850. short: T. Zisis, J. Schwarz, M. Balles, M. Kretschmer, M. Nemethova, R.P. Chait, R. Hauschild, J. Lange, C.C. Guet, M.K. Sixt, S. Zahler, ACS Applied Materials and Interfaces 13 (2021) 35545–35560. date_created: 2021-08-08T22:01:28Z date_published: 2021-08-04T00:00:00Z date_updated: 2023-08-10T14:22:48Z day: '04' ddc: - '620' - '570' department: - _id: MiSi - _id: GaTk - _id: Bio - _id: CaGu doi: 10.1021/acsami.1c09850 ec_funded: 1 external_id: isi: - '000683741400026' pmid: - '34283577' file: - access_level: open_access checksum: b043a91d9f9200e467b970b692687ed3 content_type: application/pdf creator: asandaue date_created: 2021-08-09T09:44:03Z date_updated: 2021-08-09T09:44:03Z file_id: '9833' file_name: 2021_ACSAppliedMaterialsAndInterfaces_Zisis.pdf file_size: 7123293 relation: main_file success: 1 file_date_updated: 2021-08-09T09:44:03Z has_accepted_license: '1' intvolume: ' 13' isi: 1 issue: '30' language: - iso: eng license: https://creativecommons.org/licenses/by-nc-nd/4.0/ month: '08' oa: 1 oa_version: Published Version page: 35545–35560 pmid: 1 project: - _id: 25FE9508-B435-11E9-9278-68D0E5697425 call_identifier: H2020 grant_number: '724373' name: Cellular navigation along spatial gradients publication: ACS Applied Materials and Interfaces publication_identifier: eissn: - '19448252' issn: - '19448244' publication_status: published publisher: American Chemical Society quality_controlled: '1' scopus_import: '1' status: public title: Sequential and switchable patterning for studying cellular processes under spatiotemporal control 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: 4359f0d1-fa6c-11eb-b949-802e58b17ae8 volume: 13 year: '2021' ... --- _id: '9828' abstract: - lang: eng text: Amplitude demodulation is a classical operation used in signal processing. For a long time, its effective applications in practice have been limited to narrowband signals. In this work, we generalize amplitude demodulation to wideband signals. We pose demodulation as a recovery problem of an oversampled corrupted signal and introduce special iterative schemes belonging to the family of alternating projection algorithms to solve it. Sensibly chosen structural assumptions on the demodulation outputs allow us to reveal the high inferential accuracy of the method over a rich set of relevant signals. This new approach surpasses current state-of-the-art demodulation techniques apt to wideband signals in computational efficiency by up to many orders of magnitude with no sacrifice in quality. Such performance opens the door for applications of the amplitude demodulation procedure in new contexts. In particular, the new method makes online and large-scale offline data processing feasible, including the calculation of modulator-carrier pairs in higher dimensions and poor sampling conditions, independent of the signal bandwidth. We illustrate the utility and specifics of applications of the new method in practice by using natural speech and synthetic signals. acknowledgement: The author thanks his colleagues K. Huszár and G. Tkačik for valuable discussions and comments on the manuscript. article_processing_charge: No article_type: original author: - first_name: Mantas full_name: Gabrielaitis, Mantas id: 4D5B0CBC-F248-11E8-B48F-1D18A9856A87 last_name: Gabrielaitis orcid: 0000-0002-7758-2016 citation: ama: Gabrielaitis M. Fast and accurate amplitude demodulation of wideband signals. IEEE Transactions on Signal Processing. 2021;69:4039-4054. doi:10.1109/TSP.2021.3087899 apa: Gabrielaitis, M. (2021). Fast and accurate amplitude demodulation of wideband signals. IEEE Transactions on Signal Processing. Institute of Electrical and Electronics Engineers. https://doi.org/10.1109/TSP.2021.3087899 chicago: Gabrielaitis, Mantas. “Fast and Accurate Amplitude Demodulation of Wideband Signals.” IEEE Transactions on Signal Processing. Institute of Electrical and Electronics Engineers, 2021. https://doi.org/10.1109/TSP.2021.3087899. ieee: M. Gabrielaitis, “Fast and accurate amplitude demodulation of wideband signals,” IEEE Transactions on Signal Processing, vol. 69. Institute of Electrical and Electronics Engineers, pp. 4039–4054, 2021. ista: Gabrielaitis M. 2021. Fast and accurate amplitude demodulation of wideband signals. IEEE Transactions on Signal Processing. 69, 4039–4054. mla: Gabrielaitis, Mantas. “Fast and Accurate Amplitude Demodulation of Wideband Signals.” IEEE Transactions on Signal Processing, vol. 69, Institute of Electrical and Electronics Engineers, 2021, pp. 4039–54, doi:10.1109/TSP.2021.3087899. short: M. Gabrielaitis, IEEE Transactions on Signal Processing 69 (2021) 4039–4054. date_created: 2021-08-08T22:01:31Z date_published: 2021-06-09T00:00:00Z date_updated: 2023-08-10T14:19:33Z day: '09' department: - _id: GaTk doi: 10.1109/TSP.2021.3087899 external_id: arxiv: - '2102.04832' isi: - '000682123900002' intvolume: ' 69' isi: 1 language: - iso: eng main_file_link: - open_access: '1' url: https://arxiv.org/abs/2102.04832 month: '06' oa: 1 oa_version: Preprint page: 4039 - 4054 publication: IEEE Transactions on Signal Processing publication_identifier: eissn: - 1941-0476 issn: - 1053-587X publication_status: published publisher: Institute of Electrical and Electronics Engineers quality_controlled: '1' scopus_import: '1' status: public title: Fast and accurate amplitude demodulation of wideband signals type: journal_article user_id: 4359f0d1-fa6c-11eb-b949-802e58b17ae8 volume: 69 year: '2021' ... --- _id: '9362' abstract: - lang: eng text: A central goal in systems neuroscience is to understand the functions performed by neural circuits. Previous top-down models addressed this question by comparing the behaviour of an ideal model circuit, optimised to perform a given function, with neural recordings. However, this requires guessing in advance what function is being performed, which may not be possible for many neural systems. To address this, we propose an inverse reinforcement learning (RL) framework for inferring the function performed by a neural network from data. We assume that the responses of each neuron in a network are optimised so as to drive the network towards ‘rewarded’ states, that are desirable for performing a given function. We then show how one can use inverse RL to infer the reward function optimised by the network from observing its responses. This inferred reward function can be used to predict how the neural network should adapt its dynamics to perform the same function when the external environment or network structure changes. This could lead to theoretical predictions about how neural network dynamics adapt to deal with cell death and/or varying sensory stimulus statistics. acknowledgement: The authors would like to thank Ulisse Ferrari for useful discussions and feedback. article_number: e0248940 article_processing_charge: No article_type: original 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: Gašper full_name: Tkačik, Gašper id: 3D494DCA-F248-11E8-B48F-1D18A9856A87 last_name: Tkačik orcid: 0000-0002-6699-1455 - first_name: Olivier full_name: Marre, Olivier last_name: Marre citation: ama: Chalk MJ, Tkačik G, Marre O. Inferring the function performed by a recurrent neural network. PLoS ONE. 2021;16(4). doi:10.1371/journal.pone.0248940 apa: Chalk, M. J., Tkačik, G., & Marre, O. (2021). Inferring the function performed by a recurrent neural network. PLoS ONE. Public Library of Science. https://doi.org/10.1371/journal.pone.0248940 chicago: Chalk, Matthew J, Gašper Tkačik, and Olivier Marre. “Inferring the Function Performed by a Recurrent Neural Network.” PLoS ONE. Public Library of Science, 2021. https://doi.org/10.1371/journal.pone.0248940. ieee: M. J. Chalk, G. Tkačik, and O. Marre, “Inferring the function performed by a recurrent neural network,” PLoS ONE, vol. 16, no. 4. Public Library of Science, 2021. ista: Chalk MJ, Tkačik G, Marre O. 2021. Inferring the function performed by a recurrent neural network. PLoS ONE. 16(4), e0248940. mla: Chalk, Matthew J., et al. “Inferring the Function Performed by a Recurrent Neural Network.” PLoS ONE, vol. 16, no. 4, e0248940, Public Library of Science, 2021, doi:10.1371/journal.pone.0248940. short: M.J. Chalk, G. Tkačik, O. Marre, PLoS ONE 16 (2021). date_created: 2021-05-02T22:01:28Z date_published: 2021-04-15T00:00:00Z date_updated: 2023-10-18T08:17:42Z day: '15' ddc: - '570' department: - _id: GaTk doi: 10.1371/journal.pone.0248940 external_id: isi: - '000641474900072' pmid: - '33857170' file: - access_level: open_access checksum: c52da133850307d2031f552d998f00e8 content_type: application/pdf creator: kschuh date_created: 2021-05-04T13:22:19Z date_updated: 2021-05-04T13:22:19Z file_id: '9371' file_name: 2021_pone_Chalk.pdf file_size: 2768282 relation: main_file success: 1 file_date_updated: 2021-05-04T13:22:19Z has_accepted_license: '1' intvolume: ' 16' isi: 1 issue: '4' language: - iso: eng license: https://creativecommons.org/licenses/by/4.0/ month: '04' oa: 1 oa_version: Published Version pmid: 1 publication: PLoS ONE publication_identifier: eissn: - '19326203' publication_status: published publisher: Public Library of Science quality_controlled: '1' scopus_import: '1' status: public title: Inferring the function performed by a recurrent neural network 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: 16 year: '2021' ... --- _id: '8997' abstract: - lang: eng text: Phenomenological relations such as Ohm’s or Fourier’s law have a venerable history in physics but are still scarce in biology. This situation restrains predictive theory. Here, we build on bacterial “growth laws,” which capture physiological feedback between translation and cell growth, to construct a minimal biophysical model for the combined action of ribosome-targeting antibiotics. Our model predicts drug interactions like antagonism or synergy solely from responses to individual drugs. We provide analytical results for limiting cases, which agree well with numerical results. We systematically refine the model by including direct physical interactions of different antibiotics on the ribosome. In a limiting case, our model provides a mechanistic underpinning for recent predictions of higher-order interactions that were derived using entropy maximization. We further refine the model to include the effects of antibiotics that mimic starvation and the presence of resistance genes. We describe the impact of a starvation-mimicking antibiotic on drug interactions analytically and verify it experimentally. Our extended model suggests a change in the type of drug interaction that depends on the strength of resistance, which challenges established rescaling paradigms. We experimentally show that the presence of unregulated resistance genes can lead to altered drug interaction, which agrees with the prediction of the model. While minimal, the model is readily adaptable and opens the door to predicting interactions of second and higher-order in a broad range of biological systems. acknowledgement: 'This work was supported in part by Tum stipend of Knafelj foundation (to B.K.), Austrian Science Fund (FWF) standalone grants P 27201-B22 (to T.B.) and P 28844(to G.T.), HFSP program Grant RGP0042/2013 (to T.B.), German Research Foundation (DFG) individual grant BO 3502/2-1 (to T.B.), and German Research Foundation (DFG) Collaborative Research Centre (SFB) 1310 (to T.B.). ' article_number: e1008529 article_processing_charge: Yes 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: Gašper full_name: Tkačik, Gašper id: 3D494DCA-F248-11E8-B48F-1D18A9856A87 last_name: Tkačik orcid: 0000-0002-6699-1455 - first_name: Tobias full_name: Bollenbach, Tobias id: 3E6DB97A-F248-11E8-B48F-1D18A9856A87 last_name: Bollenbach orcid: 0000-0003-4398-476X citation: ama: Kavcic B, Tkačik G, Bollenbach MT. Minimal biophysical model of combined antibiotic action. PLOS Computational Biology. 2021;17. doi:10.1371/journal.pcbi.1008529 apa: Kavcic, B., Tkačik, G., & Bollenbach, M. T. (2021). Minimal biophysical model of combined antibiotic action. PLOS Computational Biology. Public Library of Science. https://doi.org/10.1371/journal.pcbi.1008529 chicago: Kavcic, Bor, Gašper Tkačik, and Mark Tobias Bollenbach. “Minimal Biophysical Model of Combined Antibiotic Action.” PLOS Computational Biology. Public Library of Science, 2021. https://doi.org/10.1371/journal.pcbi.1008529. ieee: B. Kavcic, G. Tkačik, and M. T. Bollenbach, “Minimal biophysical model of combined antibiotic action,” PLOS Computational Biology, vol. 17. Public Library of Science, 2021. ista: Kavcic B, Tkačik G, Bollenbach MT. 2021. Minimal biophysical model of combined antibiotic action. PLOS Computational Biology. 17, e1008529. mla: Kavcic, Bor, et al. “Minimal Biophysical Model of Combined Antibiotic Action.” PLOS Computational Biology, vol. 17, e1008529, Public Library of Science, 2021, doi:10.1371/journal.pcbi.1008529. short: B. Kavcic, G. Tkačik, M.T. Bollenbach, PLOS Computational Biology 17 (2021). date_created: 2021-01-08T07:16:18Z date_published: 2021-01-07T00:00:00Z date_updated: 2024-02-21T12:41:41Z day: '07' ddc: - '570' department: - _id: GaTk doi: 10.1371/journal.pcbi.1008529 external_id: isi: - '000608045000010' file: - access_level: open_access checksum: e29f2b42651bef8e034781de8781ffac content_type: application/pdf creator: dernst date_created: 2021-02-04T12:30:48Z date_updated: 2021-02-04T12:30:48Z file_id: '9092' file_name: 2021_PlosComBio_Kavcic.pdf file_size: 3690053 relation: main_file success: 1 file_date_updated: 2021-02-04T12:30:48Z has_accepted_license: '1' intvolume: ' 17' isi: 1 keyword: - Modelling and Simulation - Genetics - Molecular Biology - Antibiotics - Drug interactions language: - iso: eng month: '01' oa: 1 oa_version: Published Version project: - _id: 25E9AF9E-B435-11E9-9278-68D0E5697425 call_identifier: FWF grant_number: P27201-B22 name: Revealing the mechanisms underlying drug interactions - _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: issn: - 1553-7358 publication_status: published publisher: Public Library of Science quality_controlled: '1' related_material: record: - id: '7673' relation: earlier_version status: public - id: '8930' relation: research_data status: public status: public title: Minimal biophysical model of combined antibiotic action 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: 17 year: '2021' ... --- _id: '9283' abstract: - lang: eng text: Gene expression levels are influenced by multiple coexisting molecular mechanisms. Some of these interactions such as those of transcription factors and promoters have been studied extensively. However, predicting phenotypes of gene regulatory networks (GRNs) remains a major challenge. Here, we use a well-defined synthetic GRN to study in Escherichia coli how network phenotypes depend on local genetic context, i.e. the genetic neighborhood of a transcription factor and its relative position. We show that one GRN with fixed topology can display not only quantitatively but also qualitatively different phenotypes, depending solely on the local genetic context of its components. Transcriptional read-through is the main molecular mechanism that places one transcriptional unit (TU) within two separate regulons without the need for complex regulatory sequences. We propose that relative order of individual TUs, with its potential for combinatorial complexity, plays an important role in shaping phenotypes of GRNs. acknowledgement: "We thank J Bollback, L Hurst, M Lagator, C Nizak, O Rivoire, M Savageau, G Tkacik, and B Vicozo\r\nfor helpful discussions; A Dolinar and A Greshnova for technical assistance; T Bollenbach for supplying the strain JW0336; C Rusnac, and members of the Guet lab for comments. 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 n˚\r\n628377 (ANS) and an Austrian Science Fund (FWF) grant n˚ I 3901-B32 (CCG)." article_number: e65993 article_processing_charge: Yes article_type: original author: - first_name: Anna A full_name: Nagy-Staron, Anna A id: 3ABC5BA6-F248-11E8-B48F-1D18A9856A87 last_name: Nagy-Staron orcid: 0000-0002-1391-8377 - first_name: Kathrin full_name: Tomasek, Kathrin id: 3AEC8556-F248-11E8-B48F-1D18A9856A87 last_name: Tomasek orcid: 0000-0003-3768-877X - first_name: Caroline full_name: Caruso Carter, Caroline last_name: Caruso Carter - first_name: Elisabeth full_name: Sonnleitner, Elisabeth last_name: Sonnleitner - first_name: Bor full_name: Kavcic, Bor id: 350F91D2-F248-11E8-B48F-1D18A9856A87 last_name: Kavcic orcid: 0000-0001-6041-254X - first_name: Tiago full_name: Paixão, Tiago last_name: Paixão - 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: Nagy-Staron AA, Tomasek K, Caruso Carter C, et al. Local genetic context shapes the function of a gene regulatory network. eLife. 2021;10. doi:10.7554/elife.65993 apa: Nagy-Staron, A. A., Tomasek, K., Caruso Carter, C., Sonnleitner, E., Kavcic, B., Paixão, T., & Guet, C. C. (2021). Local genetic context shapes the function of a gene regulatory network. ELife. eLife Sciences Publications. https://doi.org/10.7554/elife.65993 chicago: Nagy-Staron, Anna A, Kathrin Tomasek, Caroline Caruso Carter, Elisabeth Sonnleitner, Bor Kavcic, Tiago Paixão, and Calin C Guet. “Local Genetic Context Shapes the Function of a Gene Regulatory Network.” ELife. eLife Sciences Publications, 2021. https://doi.org/10.7554/elife.65993. ieee: A. A. Nagy-Staron et al., “Local genetic context shapes the function of a gene regulatory network,” eLife, vol. 10. eLife Sciences Publications, 2021. ista: Nagy-Staron AA, Tomasek K, Caruso Carter C, Sonnleitner E, Kavcic B, Paixão T, Guet CC. 2021. Local genetic context shapes the function of a gene regulatory network. eLife. 10, e65993. mla: Nagy-Staron, Anna A., et al. “Local Genetic Context Shapes the Function of a Gene Regulatory Network.” ELife, vol. 10, e65993, eLife Sciences Publications, 2021, doi:10.7554/elife.65993. short: A.A. Nagy-Staron, K. Tomasek, C. Caruso Carter, E. Sonnleitner, B. Kavcic, T. Paixão, C.C. Guet, ELife 10 (2021). date_created: 2021-03-23T10:11:46Z date_published: 2021-03-08T00:00:00Z date_updated: 2024-02-21T12:41:57Z day: '08' ddc: - '570' department: - _id: GaTk - _id: CaGu doi: 10.7554/elife.65993 ec_funded: 1 external_id: isi: - '000631050900001' file: - access_level: open_access checksum: 3c2f44058c2dd45a5a1027f09d263f8e content_type: application/pdf creator: bkavcic date_created: 2021-03-23T10:12:58Z date_updated: 2021-03-23T10:12:58Z file_id: '9284' file_name: elife-65993-v2.pdf file_size: 1390469 relation: main_file success: 1 file_date_updated: 2021-03-23T10:12:58Z has_accepted_license: '1' intvolume: ' 10' isi: 1 keyword: - Genetics and Molecular Biology language: - iso: eng month: '03' oa: 1 oa_version: Published Version project: - _id: 2517526A-B435-11E9-9278-68D0E5697425 call_identifier: FP7 grant_number: '628377' name: 'The Systems Biology of Transcriptional Read-Through in Bacteria: from Synthetic Networks to Genomic Studies' - _id: 268BFA92-B435-11E9-9278-68D0E5697425 call_identifier: FWF grant_number: I03901 name: 'CyberCircuits: Cybergenetic circuits to test composability of gene networks' publication: eLife publication_identifier: issn: - 2050-084X publication_status: published publisher: eLife Sciences Publications quality_controlled: '1' related_material: record: - id: '8951' relation: research_data status: public status: public title: Local genetic context shapes the function of a gene regulatory network 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: 10 year: '2021' ... --- _id: '7553' abstract: - lang: eng text: Normative theories and statistical inference provide complementary approaches for the study of biological systems. A normative theory postulates that organisms have adapted to efficiently solve essential tasks, and proceeds to mathematically work out testable consequences of such optimality; parameters that maximize the hypothesized organismal function can be derived ab initio, without reference to experimental data. In contrast, statistical inference focuses on efficient utilization of data to learn model parameters, without reference to any a priori notion of biological function, utility, or fitness. Traditionally, these two approaches were developed independently and applied separately. Here we unify them in a coherent Bayesian framework that embeds a normative theory into a family of maximum-entropy “optimization priors.” This family defines a smooth interpolation between a data-rich inference regime (characteristic of “bottom-up” statistical models), and a data-limited ab inito prediction regime (characteristic of “top-down” normative theory). We demonstrate the applicability of our framework using data from the visual cortex, and argue that the flexibility it affords is essential to address a number of fundamental challenges relating to inference and prediction in complex, high-dimensional biological problems. acknowledgement: The authors thank Dario Ringach for providing the V1 receptive fields and Olivier Marre for providing the retinal receptive fields. W.M. was funded by the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement no. 754411. M.H. was funded in part by Human Frontiers Science grant no. HFSP RGP0032/2018. article_processing_charge: No author: - first_name: Wiktor F full_name: Mlynarski, Wiktor F id: 358A453A-F248-11E8-B48F-1D18A9856A87 last_name: Mlynarski - 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: Mlynarski WF, Hledik M, Sokolowski TR, Tkačik G. Statistical analysis and optimality of neural systems. Neuron. 2021;109(7):1227-1241.e5. doi:10.1016/j.neuron.2021.01.020 apa: Mlynarski, W. F., Hledik, M., Sokolowski, T. R., & Tkačik, G. (2021). Statistical analysis and optimality of neural systems. Neuron. Cell Press. https://doi.org/10.1016/j.neuron.2021.01.020 chicago: Mlynarski, Wiktor F, Michal Hledik, Thomas R Sokolowski, and Gašper Tkačik. “Statistical Analysis and Optimality of Neural Systems.” Neuron. Cell Press, 2021. https://doi.org/10.1016/j.neuron.2021.01.020. ieee: W. F. Mlynarski, M. Hledik, T. R. Sokolowski, and G. Tkačik, “Statistical analysis and optimality of neural systems,” Neuron, vol. 109, no. 7. Cell Press, p. 1227–1241.e5, 2021. ista: Mlynarski WF, Hledik M, Sokolowski TR, Tkačik G. 2021. Statistical analysis and optimality of neural systems. Neuron. 109(7), 1227–1241.e5. mla: Mlynarski, Wiktor F., et al. “Statistical Analysis and Optimality of Neural Systems.” Neuron, vol. 109, no. 7, Cell Press, 2021, p. 1227–1241.e5, doi:10.1016/j.neuron.2021.01.020. short: W.F. Mlynarski, M. Hledik, T.R. Sokolowski, G. Tkačik, Neuron 109 (2021) 1227–1241.e5. date_created: 2020-02-28T11:00:12Z date_published: 2021-04-07T00:00:00Z date_updated: 2024-03-06T14:22:51Z day: '07' department: - _id: GaTk doi: 10.1016/j.neuron.2021.01.020 ec_funded: 1 external_id: isi: - '000637809600006' intvolume: ' 109' isi: 1 issue: '7' language: - iso: eng main_file_link: - open_access: '1' url: https://doi.org/10.1101/848374 month: '04' oa: 1 oa_version: Preprint page: 1227-1241.e5 project: - _id: 260C2330-B435-11E9-9278-68D0E5697425 call_identifier: H2020 grant_number: '754411' name: ISTplus - Postdoctoral Fellowships publication: Neuron 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/can-evolution-be-predicted/ record: - id: '15020' relation: dissertation_contains status: public scopus_import: '1' status: public title: Statistical analysis and optimality of neural systems type: journal_article user_id: 4359f0d1-fa6c-11eb-b949-802e58b17ae8 volume: 109 year: '2021' ... --- _id: '10077' abstract: - lang: eng text: Although much is known about how single neurons in the hippocampus represent an animal’s position, how cell-cell interactions contribute to spatial coding remains poorly understood. Using a novel statistical estimator and theoretical modeling, both developed in the framework of maximum entropy models, we reveal highly structured cell-to-cell interactions whose statistics depend on familiar vs. novel environment. In both conditions the circuit interactions optimize the encoding of spatial information, but for regimes that differ in the signal-to-noise ratio of their spatial inputs. Moreover, the topology of the interactions facilitates linear decodability, making the information easy to read out by downstream circuits. These findings suggest that the efficient coding hypothesis is not applicable only to individual neuron properties in the sensory periphery, but also to neural interactions in the central brain. acknowledgement: We thank Peter Baracskay, Karola Kaefer and Hugo Malagon-Vina for the acquisition of the data. We thank Federico Stella for comments on an earlier version of the manuscript. MN was supported by European Union Horizon 2020 grant 665385, JC was supported by European Research Council consolidator grant 281511, GT was supported by the Austrian Science Fund (FWF) grant P34015, CS was supported by an IST fellow grant, National Institute of Mental Health Award 1R01MH125571-01, by the National Science Foundation under NSF Award No. 1922658 and a Google faculty award. article_processing_charge: No author: - first_name: Michele full_name: Nardin, Michele id: 30BD0376-F248-11E8-B48F-1D18A9856A87 last_name: Nardin orcid: 0000-0001-8849-6570 - first_name: Jozsef L full_name: Csicsvari, Jozsef L id: 3FA14672-F248-11E8-B48F-1D18A9856A87 last_name: Csicsvari orcid: 0000-0002-5193-4036 - first_name: Gašper full_name: Tkačik, Gašper id: 3D494DCA-F248-11E8-B48F-1D18A9856A87 last_name: Tkačik orcid: 0000-0002-6699-1455 - first_name: Cristina full_name: Savin, Cristina id: 3933349E-F248-11E8-B48F-1D18A9856A87 last_name: Savin citation: ama: Nardin M, Csicsvari JL, Tkačik G, Savin C. The structure of hippocampal CA1 interactions optimizes spatial coding across experience. bioRxiv. doi:10.1101/2021.09.28.460602 apa: Nardin, M., Csicsvari, J. L., Tkačik, G., & Savin, C. (n.d.). The structure of hippocampal CA1 interactions optimizes spatial coding across experience. bioRxiv. Cold Spring Harbor Laboratory. https://doi.org/10.1101/2021.09.28.460602 chicago: Nardin, Michele, Jozsef L Csicsvari, Gašper Tkačik, and Cristina Savin. “The Structure of Hippocampal CA1 Interactions Optimizes Spatial Coding across Experience.” BioRxiv. Cold Spring Harbor Laboratory, n.d. https://doi.org/10.1101/2021.09.28.460602. ieee: M. Nardin, J. L. Csicsvari, G. Tkačik, and C. Savin, “The structure of hippocampal CA1 interactions optimizes spatial coding across experience,” bioRxiv. Cold Spring Harbor Laboratory. ista: Nardin M, Csicsvari JL, Tkačik G, Savin C. The structure of hippocampal CA1 interactions optimizes spatial coding across experience. bioRxiv, 10.1101/2021.09.28.460602. mla: Nardin, Michele, et al. “The Structure of Hippocampal CA1 Interactions Optimizes Spatial Coding across Experience.” BioRxiv, Cold Spring Harbor Laboratory, doi:10.1101/2021.09.28.460602. short: M. Nardin, J.L. Csicsvari, G. Tkačik, C. Savin, BioRxiv (n.d.). date_created: 2021-10-04T06:23:34Z date_published: 2021-09-29T00:00:00Z date_updated: 2024-03-27T23:30:16Z day: '29' department: - _id: GradSch - _id: JoCs - _id: GaTk doi: 10.1101/2021.09.28.460602 ec_funded: 1 language: - iso: eng main_file_link: - open_access: '1' url: https://www.biorxiv.org/content/10.1101/2021.09.28.460602 month: '09' oa: 1 oa_version: Preprint project: - _id: 25681D80-B435-11E9-9278-68D0E5697425 call_identifier: FP7 grant_number: '291734' name: International IST Postdoc Fellowship Programme - _id: 2564DBCA-B435-11E9-9278-68D0E5697425 call_identifier: H2020 grant_number: '665385' name: International IST Doctoral Program - _id: 257A4776-B435-11E9-9278-68D0E5697425 call_identifier: FP7 grant_number: '281511' name: Memory-related information processing in neuronal circuits of the hippocampus and entorhinal cortex - _id: 626c45b5-2b32-11ec-9570-e509828c1ba6 grant_number: P34015 name: Efficient coding with biophysical realism publication: bioRxiv publication_status: submitted publisher: Cold Spring Harbor Laboratory related_material: record: - id: '11932' relation: dissertation_contains status: public status: public title: The structure of hippocampal CA1 interactions optimizes spatial coding across experience 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: preprint user_id: 8b945eb4-e2f2-11eb-945a-df72226e66a9 year: '2021' ... --- _id: '8105' abstract: - lang: eng text: Physical and biological systems often exhibit intermittent dynamics with bursts or avalanches (active states) characterized by power-law size and duration distributions. These emergent features are typical of systems at the critical point of continuous phase transitions, and have led to the hypothesis that such systems may self-organize at criticality, i.e. without any fine tuning of parameters. Since the introduction of the Bak-Tang-Wiesenfeld (BTW) model, the paradigm of self-organized criticality (SOC) has been very fruitful for the analysis of emergent collective behaviors in a number of systems, including the brain. Although considerable effort has been devoted in identifying and modeling scaling features of burst and avalanche statistics, dynamical aspects related to the temporal organization of bursts remain often poorly understood or controversial. Of crucial importance to understand the mechanisms responsible for emergent behaviors is the relationship between active and quiet periods, and the nature of the correlations. Here we investigate the dynamics of active (θ-bursts) and quiet states (δ-bursts) in brain activity during the sleep-wake cycle. We show the duality of power-law (θ, active phase) and exponential-like (δ, quiescent phase) duration distributions, typical of SOC, jointly emerge with power-law temporal correlations and anti-correlated coupling between active and quiet states. Importantly, we demonstrate that such temporal organization shares important similarities with earthquake dynamics, and propose that specific power-law correlations and coupling between active and quiet states are distinctive characteristics of a class of systems with self-organization at criticality. article_number: '00005' article_processing_charge: No article_type: original author: - first_name: Fabrizio full_name: Lombardi, Fabrizio id: A057D288-3E88-11E9-986D-0CF4E5697425 last_name: Lombardi orcid: 0000-0003-2623-5249 - first_name: Jilin W.J.L. full_name: Wang, Jilin W.J.L. last_name: Wang - first_name: Xiyun full_name: Zhang, Xiyun last_name: Zhang - first_name: Plamen Ch full_name: Ivanov, Plamen Ch last_name: Ivanov citation: ama: Lombardi F, Wang JWJL, Zhang X, Ivanov PC. Power-law correlations and coupling of active and quiet states underlie a class of complex systems with self-organization at criticality. EPJ Web of Conferences. 2020;230. doi:10.1051/epjconf/202023000005 apa: Lombardi, F., Wang, J. W. J. L., Zhang, X., & Ivanov, P. C. (2020). Power-law correlations and coupling of active and quiet states underlie a class of complex systems with self-organization at criticality. EPJ Web of Conferences. EDP Sciences. https://doi.org/10.1051/epjconf/202023000005 chicago: Lombardi, Fabrizio, Jilin W.J.L. Wang, Xiyun Zhang, and Plamen Ch Ivanov. “Power-Law Correlations and Coupling of Active and Quiet States Underlie a Class of Complex Systems with Self-Organization at Criticality.” EPJ Web of Conferences. EDP Sciences, 2020. https://doi.org/10.1051/epjconf/202023000005. ieee: F. Lombardi, J. W. J. L. Wang, X. Zhang, and P. C. Ivanov, “Power-law correlations and coupling of active and quiet states underlie a class of complex systems with self-organization at criticality,” EPJ Web of Conferences, vol. 230. EDP Sciences, 2020. ista: Lombardi F, Wang JWJL, Zhang X, Ivanov PC. 2020. Power-law correlations and coupling of active and quiet states underlie a class of complex systems with self-organization at criticality. EPJ Web of Conferences. 230, 00005. mla: Lombardi, Fabrizio, et al. “Power-Law Correlations and Coupling of Active and Quiet States Underlie a Class of Complex Systems with Self-Organization at Criticality.” EPJ Web of Conferences, vol. 230, 00005, EDP Sciences, 2020, doi:10.1051/epjconf/202023000005. short: F. Lombardi, J.W.J.L. Wang, X. Zhang, P.C. Ivanov, EPJ Web of Conferences 230 (2020). date_created: 2020-07-12T16:20:33Z date_published: 2020-03-11T00:00:00Z date_updated: 2021-01-12T08:16:55Z day: '11' ddc: - '530' department: - _id: GaTk doi: 10.1051/epjconf/202023000005 file: - access_level: open_access content_type: application/pdf creator: dernst date_created: 2020-07-22T06:17:11Z date_updated: 2020-07-22T06:17:11Z file_id: '8144' file_name: 2020_EPJWebConf_Lombardi.pdf file_size: 2197543 relation: main_file success: 1 file_date_updated: 2020-07-22T06:17:11Z has_accepted_license: '1' intvolume: ' 230' language: - iso: eng month: '03' oa: 1 oa_version: Published Version publication: EPJ Web of Conferences publication_identifier: issn: - 2100-014X publication_status: published publisher: EDP Sciences quality_controlled: '1' status: public title: Power-law correlations and coupling of active and quiet states underlie a class of complex systems with self-organization at 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: 2DF688A6-F248-11E8-B48F-1D18A9856A87 volume: 230 year: '2020' ...