--- _id: '11638' abstract: - lang: eng text: 'Statistical inference is central to many scientific endeavors, yet how it works remains unresolved. Answering this requires a quantitative understanding of the intrinsic interplay between statistical models, inference methods, and the structure in the data. To this end, we characterize the efficacy of direct coupling analysis (DCA)—a highly successful method for analyzing amino acid sequence data—in inferring pairwise interactions from samples of ferromagnetic Ising models on random graphs. Our approach allows for physically motivated exploration of qualitatively distinct data regimes separated by phase transitions. We show that inference quality depends strongly on the nature of data-generating distributions: optimal accuracy occurs at an intermediate temperature where the detrimental effects from macroscopic order and thermal noise are minimal. Importantly our results indicate that DCA does not always outperform its local-statistics-based predecessors; while DCA excels at low temperatures, it becomes inferior to simple correlation thresholding at virtually all temperatures when data are limited. Our findings offer insights into the regime in which DCA operates so successfully, and more broadly, how inference interacts with the structure in the data.' acknowledgement: This work was supported in part by the Alfred P. Sloan Foundation, the Simons Foundation, the National Institutes of Health under Award No. R01EB026943, and the National Science Foundation, through the Center for the Physics of Biological Function (PHY-1734030). article_number: '023240' article_processing_charge: No article_type: original author: - first_name: Vudtiwat full_name: Ngampruetikorn, Vudtiwat last_name: Ngampruetikorn - first_name: Vedant full_name: Sachdeva, Vedant last_name: Sachdeva - first_name: Johanna full_name: Torrence, Johanna last_name: Torrence - first_name: Jan full_name: Humplik, Jan id: 2E9627A8-F248-11E8-B48F-1D18A9856A87 last_name: Humplik - first_name: David J. full_name: Schwab, David J. last_name: Schwab - first_name: Stephanie E. full_name: Palmer, Stephanie E. last_name: Palmer citation: ama: Ngampruetikorn V, Sachdeva V, Torrence J, Humplik J, Schwab DJ, Palmer SE. Inferring couplings in networks across order-disorder phase transitions. Physical Review Research. 2022;4(2). doi:10.1103/PhysRevResearch.4.023240 apa: Ngampruetikorn, V., Sachdeva, V., Torrence, J., Humplik, J., Schwab, D. J., & Palmer, S. E. (2022). Inferring couplings in networks across order-disorder phase transitions. Physical Review Research. American Physical Society. https://doi.org/10.1103/PhysRevResearch.4.023240 chicago: Ngampruetikorn, Vudtiwat, Vedant Sachdeva, Johanna Torrence, Jan Humplik, David J. Schwab, and Stephanie E. Palmer. “Inferring Couplings in Networks across Order-Disorder Phase Transitions.” Physical Review Research. American Physical Society, 2022. https://doi.org/10.1103/PhysRevResearch.4.023240. ieee: V. Ngampruetikorn, V. Sachdeva, J. Torrence, J. Humplik, D. J. Schwab, and S. E. Palmer, “Inferring couplings in networks across order-disorder phase transitions,” Physical Review Research, vol. 4, no. 2. American Physical Society, 2022. ista: Ngampruetikorn V, Sachdeva V, Torrence J, Humplik J, Schwab DJ, Palmer SE. 2022. Inferring couplings in networks across order-disorder phase transitions. Physical Review Research. 4(2), 023240. mla: Ngampruetikorn, Vudtiwat, et al. “Inferring Couplings in Networks across Order-Disorder Phase Transitions.” Physical Review Research, vol. 4, no. 2, 023240, American Physical Society, 2022, doi:10.1103/PhysRevResearch.4.023240. short: V. Ngampruetikorn, V. Sachdeva, J. Torrence, J. Humplik, D.J. Schwab, S.E. Palmer, Physical Review Research 4 (2022). date_created: 2022-07-24T22:01:42Z date_published: 2022-06-24T00:00:00Z date_updated: 2022-07-25T07:52:35Z day: '24' ddc: - '530' department: - _id: GaTk doi: 10.1103/PhysRevResearch.4.023240 external_id: arxiv: - '2106.02349' file: - access_level: open_access checksum: ed6fdc2a3a096df785fa5f7b17b716c6 content_type: application/pdf creator: dernst date_created: 2022-07-25T07:47:23Z date_updated: 2022-07-25T07:47:23Z file_id: '11644' file_name: 2022_PhysicalReviewResearch_Ngampruetikorn.pdf file_size: 1379683 relation: main_file success: 1 file_date_updated: 2022-07-25T07:47:23Z funded_apc: '1' has_accepted_license: '1' intvolume: ' 4' issue: '2' language: - iso: eng license: https://creativecommons.org/licenses/by/4.0/ month: '06' oa: 1 oa_version: Published Version publication: Physical Review Research publication_identifier: issn: - 2643-1564 publication_status: published publisher: American Physical Society quality_controlled: '1' scopus_import: '1' status: public title: Inferring couplings in networks across order-disorder 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: 2DF688A6-F248-11E8-B48F-1D18A9856A87 volume: 4 year: '2022' ... --- _id: '12156' abstract: - lang: eng text: Models of transcriptional regulation that assume equilibrium binding of transcription factors have been less successful at predicting gene expression from sequence in eukaryotes than in bacteria. This could be due to the non-equilibrium nature of eukaryotic regulation. Unfortunately, the space of possible non-equilibrium mechanisms is vast and predominantly uninteresting. The key question is therefore how this space can be navigated efficiently, to focus on mechanisms and models that are biologically relevant. In this review, we advocate for the normative role of theory—theory that prescribes rather than just describes—in providing such a focus. Theory should expand its remit beyond inferring mechanistic models from data, towards identifying non-equilibrium gene regulatory schemes that may have been evolutionarily selected, despite their energy consumption, because they are precise, reliable, fast, or otherwise outperform regulation at equilibrium. We illustrate our reasoning by toy examples for which we provide simulation code. acknowledgement: 'This work was supported through the Center for the Physics of Biological Function (PHYe1734030) and by National Institutes of Health Grants R01GM097275 and U01DK127429 (TG). GT acknowledges the support of the Austrian Science Fund grant FWF P28844 and the Human Frontiers Science Program. ' article_number: '100435' article_processing_charge: Yes (via OA deal) article_type: original author: - first_name: Benjamin full_name: Zoller, Benjamin last_name: Zoller - first_name: Thomas full_name: Gregor, Thomas last_name: Gregor - first_name: Gašper full_name: Tkačik, Gašper id: 3D494DCA-F248-11E8-B48F-1D18A9856A87 last_name: Tkačik orcid: '1' citation: ama: Zoller B, Gregor T, Tkačik G. Eukaryotic gene regulation at equilibrium, or non? Current Opinion in Systems Biology. 2022;31(9). doi:10.1016/j.coisb.2022.100435 apa: Zoller, B., Gregor, T., & Tkačik, G. (2022). Eukaryotic gene regulation at equilibrium, or non? Current Opinion in Systems Biology. Elsevier. https://doi.org/10.1016/j.coisb.2022.100435 chicago: Zoller, Benjamin, Thomas Gregor, and Gašper Tkačik. “Eukaryotic Gene Regulation at Equilibrium, or Non?” Current Opinion in Systems Biology. Elsevier, 2022. https://doi.org/10.1016/j.coisb.2022.100435. ieee: B. Zoller, T. Gregor, and G. Tkačik, “Eukaryotic gene regulation at equilibrium, or non?,” Current Opinion in Systems Biology, vol. 31, no. 9. Elsevier, 2022. ista: Zoller B, Gregor T, Tkačik G. 2022. Eukaryotic gene regulation at equilibrium, or non? Current Opinion in Systems Biology. 31(9), 100435. mla: Zoller, Benjamin, et al. “Eukaryotic Gene Regulation at Equilibrium, or Non?” Current Opinion in Systems Biology, vol. 31, no. 9, 100435, Elsevier, 2022, doi:10.1016/j.coisb.2022.100435. short: B. Zoller, T. Gregor, G. Tkačik, Current Opinion in Systems Biology 31 (2022). date_created: 2023-01-12T12:08:51Z date_published: 2022-09-01T00:00:00Z date_updated: 2023-02-13T09:20:34Z day: '01' ddc: - '570' department: - _id: GaTk doi: 10.1016/j.coisb.2022.100435 file: - access_level: open_access checksum: 97ef01e0cc60cdc84f45640a0f248fb0 content_type: application/pdf creator: dernst date_created: 2023-01-24T12:14:10Z date_updated: 2023-01-24T12:14:10Z file_id: '12362' file_name: 2022_CurrentBiology_Zoller.pdf file_size: 2214944 relation: main_file success: 1 file_date_updated: 2023-01-24T12:14:10Z has_accepted_license: '1' intvolume: ' 31' issue: '9' keyword: - Applied Mathematics - Computer Science Applications - Drug Discovery - General Biochemistry - Genetics and Molecular Biology - Modeling and Simulation language: - iso: eng month: '09' 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 publication: Current Opinion in Systems Biology publication_identifier: issn: - 2452-3100 publication_status: published publisher: Elsevier quality_controlled: '1' scopus_import: '1' status: public title: Eukaryotic gene regulation at equilibrium, or non? 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: 31 year: '2022' ... --- _id: '10530' abstract: - lang: eng text: "Cell dispersion from a confined area is fundamental in a number of biological processes,\r\nincluding cancer metastasis. To date, a quantitative understanding of the interplay of single\r\ncell motility, cell proliferation, and intercellular contacts remains elusive. In particular, the role\r\nof E- and N-Cadherin junctions, central components of intercellular contacts, is still\r\ncontroversial. Combining theoretical modeling with in vitro observations, we investigate the\r\ncollective spreading behavior of colonies of human cancer cells (T24). The spreading of these\r\ncolonies is driven by stochastic single-cell migration with frequent transient cell-cell contacts.\r\nWe find that inhibition of E- and N-Cadherin junctions decreases colony spreading and average\r\nspreading velocities, without affecting the strength of correlations in spreading velocities of\r\nneighboring cells. Based on a biophysical simulation model for cell migration, we show that the\r\nbehavioral changes upon disruption of these junctions can be explained by reduced repulsive\r\nexcluded volume interactions between cells. This suggests that in cancer cell migration,\r\ncadherin-based intercellular contacts sharpen cell boundaries leading to repulsive rather than\r\ncohesive interactions between cells, thereby promoting efficient cell spreading during collective\r\nmigration.\r\n" acknowledgement: Funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) - Project-ID 201269156 - SFB 1032 (Projects B8 and B12). D.B.B. is supported in part by a DFG fellowship within the Graduate School of Quantitative Biosciences Munich (QBM) and by the Joachim Herz Stiftung. article_processing_charge: No article_type: original author: - first_name: Themistoklis full_name: Zisis, Themistoklis last_name: Zisis - first_name: David full_name: Brückner, David id: e1e86031-6537-11eb-953a-f7ab92be508d last_name: Brückner orcid: 0000-0001-7205-2975 - first_name: Tom full_name: Brandstätter, Tom last_name: Brandstätter - first_name: Wei Xiong full_name: Siow, Wei Xiong last_name: Siow - first_name: Joseph full_name: d’Alessandro, Joseph last_name: d’Alessandro - first_name: Angelika M. full_name: Vollmar, Angelika M. last_name: Vollmar - first_name: Chase P. full_name: Broedersz, Chase P. last_name: Broedersz - first_name: Stefan full_name: Zahler, Stefan last_name: Zahler citation: ama: Zisis T, Brückner D, Brandstätter T, et al. Disentangling cadherin-mediated cell-cell interactions in collective cancer cell migration. Biophysical Journal. 2022;121(1):P44-60. doi:10.1016/j.bpj.2021.12.006 apa: Zisis, T., Brückner, D., Brandstätter, T., Siow, W. X., d’Alessandro, J., Vollmar, A. M., … Zahler, S. (2022). Disentangling cadherin-mediated cell-cell interactions in collective cancer cell migration. Biophysical Journal. Elsevier. https://doi.org/10.1016/j.bpj.2021.12.006 chicago: Zisis, Themistoklis, David Brückner, Tom Brandstätter, Wei Xiong Siow, Joseph d’Alessandro, Angelika M. Vollmar, Chase P. Broedersz, and Stefan Zahler. “Disentangling Cadherin-Mediated Cell-Cell Interactions in Collective Cancer Cell Migration.” Biophysical Journal. Elsevier, 2022. https://doi.org/10.1016/j.bpj.2021.12.006. ieee: T. Zisis et al., “Disentangling cadherin-mediated cell-cell interactions in collective cancer cell migration,” Biophysical Journal, vol. 121, no. 1. Elsevier, pp. P44-60, 2022. ista: Zisis T, Brückner D, Brandstätter T, Siow WX, d’Alessandro J, Vollmar AM, Broedersz CP, Zahler S. 2022. Disentangling cadherin-mediated cell-cell interactions in collective cancer cell migration. Biophysical Journal. 121(1), P44-60. mla: Zisis, Themistoklis, et al. “Disentangling Cadherin-Mediated Cell-Cell Interactions in Collective Cancer Cell Migration.” Biophysical Journal, vol. 121, no. 1, Elsevier, 2022, pp. P44-60, doi:10.1016/j.bpj.2021.12.006. short: T. Zisis, D. Brückner, T. Brandstätter, W.X. Siow, J. d’Alessandro, A.M. Vollmar, C.P. Broedersz, S. Zahler, Biophysical Journal 121 (2022) P44-60. date_created: 2021-12-10T09:48:19Z date_published: 2022-01-04T00:00:00Z date_updated: 2023-08-02T13:34:25Z day: '04' ddc: - '570' department: - _id: EdHa - _id: GaTk doi: 10.1016/j.bpj.2021.12.006 external_id: isi: - '000740815400007' file: - access_level: open_access checksum: 1aa7c3478e0c8256b973b632efd1f6b4 content_type: application/pdf creator: dernst date_created: 2022-07-29T10:17:10Z date_updated: 2022-07-29T10:17:10Z file_id: '11697' file_name: 2022_BiophysicalJour_Zisis.pdf file_size: 4475504 relation: main_file success: 1 file_date_updated: 2022-07-29T10:17:10Z has_accepted_license: '1' intvolume: ' 121' isi: 1 issue: '1' keyword: - Biophysics language: - iso: eng license: https://creativecommons.org/licenses/by-nc-nd/4.0/ month: '01' oa: 1 oa_version: Published Version page: P44-60 project: - _id: 9B861AAC-BA93-11EA-9121-9846C619BF3A name: NOMIS Fellowship Program publication: Biophysical Journal publication_identifier: issn: - 0006-3495 publication_status: published publisher: Elsevier quality_controlled: '1' status: public title: Disentangling cadherin-mediated cell-cell interactions in collective cancer cell migration 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: 121 year: '2022' ... --- _id: '10736' abstract: - lang: eng text: Predicting function from sequence is a central problem of biology. Currently, this is possible only locally in a narrow mutational neighborhood around a wildtype sequence rather than globally from any sequence. Using random mutant libraries, we developed a biophysical model that accounts for multiple features of σ70 binding bacterial promoters to predict constitutive gene expression levels from any sequence. We experimentally and theoretically estimated that 10–20% of random sequences lead to expression and ~80% of non-expressing sequences are one mutation away from a functional promoter. The potential for generating expression from random sequences is so pervasive that selection acts against σ70-RNA polymerase binding sites even within inter-genic, promoter-containing regions. This pervasiveness of σ70-binding sites implies that emergence of promoters is not the limiting step in gene regulatory evolution. Ultimately, the inclusion of novel features of promoter function into a mechanistic model enabled not only more accurate predictions of gene expression levels, but also identified that promoters evolve more rapidly than previously thought. acknowledgement: 'We thank Hande Acar, Nicholas H Barton, Rok Grah, Tiago Paixao, Maros Pleska, Anna Staron, and Murat Tugrul for insightful comments and input on the manuscript. This work was supported by: Sir Henry Dale Fellowship jointly funded by the Wellcome Trust and the Royal Society (grant number 216779/Z/19/Z) to ML; IPC Grant from IST Austria to ML and SS; European Research Council Funding Programme 7 (2007–2013, grant agreement number 648440) to JPB.' article_number: e64543 article_processing_charge: No article_type: original author: - first_name: Mato full_name: Lagator, Mato id: 345D25EC-F248-11E8-B48F-1D18A9856A87 last_name: Lagator - first_name: Srdjan full_name: Sarikas, Srdjan id: 35F0286E-F248-11E8-B48F-1D18A9856A87 last_name: Sarikas - first_name: Magdalena full_name: Steinrueck, Magdalena last_name: Steinrueck - first_name: David full_name: Toledo-Aparicio, David last_name: Toledo-Aparicio - 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 - first_name: Gašper full_name: Tkačik, Gašper id: 3D494DCA-F248-11E8-B48F-1D18A9856A87 last_name: Tkačik orcid: 0000-0002-6699-1455 citation: ama: Lagator M, Sarikas S, Steinrueck M, et al. Predicting bacterial promoter function and evolution from random sequences. eLife. 2022;11. doi:10.7554/eLife.64543 apa: Lagator, M., Sarikas, S., Steinrueck, M., Toledo-Aparicio, D., Bollback, J. P., Guet, C. C., & Tkačik, G. (2022). Predicting bacterial promoter function and evolution from random sequences. ELife. eLife Sciences Publications. https://doi.org/10.7554/eLife.64543 chicago: Lagator, Mato, Srdjan Sarikas, Magdalena Steinrueck, David Toledo-Aparicio, Jonathan P Bollback, Calin C Guet, and Gašper Tkačik. “Predicting Bacterial Promoter Function and Evolution from Random Sequences.” ELife. eLife Sciences Publications, 2022. https://doi.org/10.7554/eLife.64543. ieee: M. Lagator et al., “Predicting bacterial promoter function and evolution from random sequences,” eLife, vol. 11. eLife Sciences Publications, 2022. ista: Lagator M, Sarikas S, Steinrueck M, Toledo-Aparicio D, Bollback JP, Guet CC, Tkačik G. 2022. Predicting bacterial promoter function and evolution from random sequences. eLife. 11, e64543. mla: Lagator, Mato, et al. “Predicting Bacterial Promoter Function and Evolution from Random Sequences.” ELife, vol. 11, e64543, eLife Sciences Publications, 2022, doi:10.7554/eLife.64543. short: M. Lagator, S. Sarikas, M. Steinrueck, D. Toledo-Aparicio, J.P. Bollback, C.C. Guet, G. Tkačik, ELife 11 (2022). date_created: 2022-02-06T23:01:32Z date_published: 2022-01-26T00:00:00Z date_updated: 2023-08-02T14:09:02Z day: '26' ddc: - '576' department: - _id: CaGu - _id: GaTk - _id: NiBa doi: 10.7554/eLife.64543 ec_funded: 1 external_id: isi: - '000751104400001' pmid: - '35080492' file: - access_level: open_access checksum: decdcdf600ff51e9a9703b49ca114170 content_type: application/pdf creator: cchlebak date_created: 2022-02-07T07:14:09Z date_updated: 2022-02-07T07:14:09Z file_id: '10739' file_name: 2022_ELife_Lagator.pdf file_size: 5604343 relation: main_file success: 1 file_date_updated: 2022-02-07T07:14:09Z has_accepted_license: '1' intvolume: ' 11' isi: 1 language: - iso: eng month: '01' oa: 1 oa_version: Published Version pmid: 1 project: - _id: 2578D616-B435-11E9-9278-68D0E5697425 call_identifier: H2020 grant_number: '648440' name: Selective Barriers to Horizontal Gene Transfer publication: eLife publication_identifier: eissn: - 2050-084X publication_status: published publisher: eLife Sciences Publications quality_controlled: '1' scopus_import: '1' status: public title: Predicting bacterial promoter function and evolution from random sequences 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: 11 year: '2022' ... --- _id: '12332' abstract: - lang: eng text: Activity of sensory neurons is driven not only by external stimuli but also by feedback signals from higher brain areas. Attention is one particularly important internal signal whose presumed role is to modulate sensory representations such that they only encode information currently relevant to the organism at minimal cost. This hypothesis has, however, not yet been expressed in a normative computational framework. Here, by building on normative principles of probabilistic inference and efficient coding, we developed a model of dynamic population coding in the visual cortex. By continuously adapting the sensory code to changing demands of the perceptual observer, an attention-like modulation emerges. This modulation can dramatically reduce the amount of neural activity without deteriorating the accuracy of task-specific inferences. Our results suggest that a range of seemingly disparate cortical phenomena such as intrinsic gain modulation, attention-related tuning modulation, and response variability could be manifestations of the same underlying principles, which combine efficient sensory coding with optimal probabilistic inference in dynamic environments. acknowledgement: "We thank Robbe Goris for generously providing figures from his work and Ann M. Hermundstad for helpful discussions.\r\nGT & WM were supported by the Austrian Science Fund Standalone Grant P 34015 \"Efficient Coding with Biophysical Realism\" (https://pf.fwf.ac.at/) WM was additionally supported by the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie Grant Agreement No. 754411 (https://ec.europa.eu/research/mariecurieactions/). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript." 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: Gašper full_name: Tkačik, Gašper id: 3D494DCA-F248-11E8-B48F-1D18A9856A87 last_name: Tkačik orcid: '1' citation: ama: Mlynarski WF, Tkačik G. Efficient coding theory of dynamic attentional modulation. PLoS Biology. 2022;20(12):e3001889. doi:10.1371/journal.pbio.3001889 apa: Mlynarski, W. F., & Tkačik, G. (2022). Efficient coding theory of dynamic attentional modulation. PLoS Biology. Public Library of Science. https://doi.org/10.1371/journal.pbio.3001889 chicago: Mlynarski, Wiktor F, and Gašper Tkačik. “Efficient Coding Theory of Dynamic Attentional Modulation.” PLoS Biology. Public Library of Science, 2022. https://doi.org/10.1371/journal.pbio.3001889. ieee: W. F. Mlynarski and G. Tkačik, “Efficient coding theory of dynamic attentional modulation,” PLoS Biology, vol. 20, no. 12. Public Library of Science, p. e3001889, 2022. ista: Mlynarski WF, Tkačik G. 2022. Efficient coding theory of dynamic attentional modulation. PLoS Biology. 20(12), e3001889. mla: Mlynarski, Wiktor F., and Gašper Tkačik. “Efficient Coding Theory of Dynamic Attentional Modulation.” PLoS Biology, vol. 20, no. 12, Public Library of Science, 2022, p. e3001889, doi:10.1371/journal.pbio.3001889. short: W.F. Mlynarski, G. Tkačik, PLoS Biology 20 (2022) e3001889. date_created: 2023-01-22T23:00:55Z date_published: 2022-12-21T00:00:00Z date_updated: 2023-08-03T14:23:49Z day: '21' ddc: - '570' department: - _id: GaTk doi: 10.1371/journal.pbio.3001889 ec_funded: 1 external_id: isi: - '000925192000001' file: - access_level: open_access checksum: 5d7f1111a87e5f2c1bf92f8886738894 content_type: application/pdf creator: dernst date_created: 2023-01-23T08:46:40Z date_updated: 2023-01-23T08:46:40Z file_id: '12337' file_name: 2022_PloSBiology_Mlynarski.pdf file_size: 4248838 relation: main_file success: 1 file_date_updated: 2023-01-23T08:46:40Z has_accepted_license: '1' intvolume: ' 20' isi: 1 issue: '12' language: - iso: eng month: '12' oa: 1 oa_version: Published Version page: e3001889 project: - _id: 626c45b5-2b32-11ec-9570-e509828c1ba6 grant_number: P34015 name: Efficient coding with biophysical realism - _id: 260C2330-B435-11E9-9278-68D0E5697425 call_identifier: H2020 grant_number: '754411' name: ISTplus - Postdoctoral Fellowships publication: PLoS Biology publication_identifier: eissn: - 1545-7885 publication_status: published publisher: Public Library of Science quality_controlled: '1' scopus_import: '1' status: public title: Efficient coding theory of dynamic attentional modulation 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: 20 year: '2022' ...