--- _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: '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: '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: '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: '1576' abstract: - lang: eng text: 'Gene expression is controlled primarily by interactions between transcription factor proteins (TFs) and the regulatory DNA sequence, a process that can be captured well by thermodynamic models of regulation. These models, however, neglect regulatory crosstalk: the possibility that noncognate TFs could initiate transcription, with potentially disastrous effects for the cell. Here, we estimate the importance of crosstalk, suggest that its avoidance strongly constrains equilibrium models of TF binding, and propose an alternative nonequilibrium scheme that implements kinetic proofreading to suppress erroneous initiation. This proposal is consistent with the observed covalent modifications of the transcriptional apparatus and predicts increased noise in gene expression as a trade-off for improved specificity. Using information theory, we quantify this trade-off to find when optimal proofreading architectures are favored over their equilibrium counterparts. Such architectures exhibit significant super-Poisson noise at low expression in steady state.' article_number: '248101' author: - first_name: Sarah A full_name: Cepeda Humerez, Sarah A id: 3DEE19A4-F248-11E8-B48F-1D18A9856A87 last_name: Cepeda Humerez - first_name: Georg full_name: Rieckh, Georg id: 34DA8BD6-F248-11E8-B48F-1D18A9856A87 last_name: Rieckh - first_name: Gasper full_name: Tkacik, Gasper id: 3D494DCA-F248-11E8-B48F-1D18A9856A87 last_name: Tkacik orcid: 0000-0002-6699-1455 citation: ama: Cepeda Humerez SA, Rieckh G, Tkačik G. Stochastic proofreading mechanism alleviates crosstalk in transcriptional regulation. Physical Review Letters. 2015;115(24). doi:10.1103/PhysRevLett.115.248101 apa: Cepeda Humerez, S. A., Rieckh, G., & Tkačik, G. (2015). Stochastic proofreading mechanism alleviates crosstalk in transcriptional regulation. Physical Review Letters. American Physical Society. https://doi.org/10.1103/PhysRevLett.115.248101 chicago: Cepeda Humerez, Sarah A, Georg Rieckh, and Gašper Tkačik. “Stochastic Proofreading Mechanism Alleviates Crosstalk in Transcriptional Regulation.” Physical Review Letters. American Physical Society, 2015. https://doi.org/10.1103/PhysRevLett.115.248101. ieee: S. A. Cepeda Humerez, G. Rieckh, and G. Tkačik, “Stochastic proofreading mechanism alleviates crosstalk in transcriptional regulation,” Physical Review Letters, vol. 115, no. 24. American Physical Society, 2015. ista: Cepeda Humerez SA, Rieckh G, Tkačik G. 2015. Stochastic proofreading mechanism alleviates crosstalk in transcriptional regulation. Physical Review Letters. 115(24), 248101. mla: Cepeda Humerez, Sarah A., et al. “Stochastic Proofreading Mechanism Alleviates Crosstalk in Transcriptional Regulation.” Physical Review Letters, vol. 115, no. 24, 248101, American Physical Society, 2015, doi:10.1103/PhysRevLett.115.248101. short: S.A. Cepeda Humerez, G. Rieckh, G. Tkačik, Physical Review Letters 115 (2015). date_created: 2018-12-11T11:52:49Z date_published: 2015-12-08T00:00:00Z date_updated: 2023-09-07T12:55:21Z day: '08' department: - _id: GaTk doi: 10.1103/PhysRevLett.115.248101 ec_funded: 1 intvolume: ' 115' issue: '24' language: - iso: eng main_file_link: - open_access: '1' url: http://arxiv.org/abs/1504.05716 month: '12' oa: 1 oa_version: Preprint project: - _id: 25B07788-B435-11E9-9278-68D0E5697425 call_identifier: FP7 grant_number: '250152' name: Limits to selection in biology and in evolutionary computation publication: Physical Review Letters publication_status: published publisher: American Physical Society publist_id: '5595' quality_controlled: '1' related_material: record: - id: '6473' relation: part_of_dissertation status: public scopus_import: 1 status: public title: Stochastic proofreading mechanism alleviates crosstalk in transcriptional regulation type: journal_article user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87 volume: 115 year: '2015' ...