[{"language":[{"iso":"eng"}],"department":[{"_id":"GradSch"},{"_id":"NiBa"},{"_id":"GaTk"}],"type":"dissertation","page":"158","date_created":"2024-02-23T14:02:04Z","has_accepted_license":"1","related_material":{"record":[{"id":"7553","relation":"part_of_dissertation","status":"public"},{"id":"7606","relation":"part_of_dissertation","status":"public"},{"id":"12081","relation":"part_of_dissertation","status":"public"}]},"keyword":["Theoretical biology","Optimality","Evolution","Information"],"article_processing_charge":"No","file":[{"file_size":7102089,"success":1,"content_type":"application/pdf","relation":"main_file","date_created":"2024-02-23T13:50:53Z","date_updated":"2024-02-23T13:50:53Z","file_name":"hledik thesis pdfa 2b.pdf","access_level":"open_access","file_id":"15021","creator":"mhledik","checksum":"b2d3da47c98d481577a4baf68944fe41"},{"file_name":"hledik thesis source.zip","date_updated":"2024-02-23T14:20:16Z","date_created":"2024-02-23T13:50:54Z","checksum":"eda9b9430da2610fee7ce1c1419a479a","creator":"mhledik","file_id":"15022","access_level":"closed","relation":"source_file","content_type":"application/zip","file_size":14014790}],"project":[{"name":"International IST Doctoral Program","call_identifier":"H2020","_id":"2564DBCA-B435-11E9-9278-68D0E5697425","grant_number":"665385"},{"_id":"2665AAFE-B435-11E9-9278-68D0E5697425","grant_number":"RGP0034/2018","name":"Can evolution minimize spurious signaling crosstalk to reach optimal performance?"},{"grant_number":"101055327","_id":"bd6958e0-d553-11ed-ba76-86eba6a76c00","name":"Understanding the evolution of continuous genomes"}],"author":[{"id":"4171253A-F248-11E8-B48F-1D18A9856A87","last_name":"Hledik","first_name":"Michal","full_name":"Hledik, Michal"}],"day":"23","supervisor":[{"full_name":"Barton, Nicholas H","orcid":"0000-0002-8548-5240","first_name":"Nicholas H","id":"4880FE40-F248-11E8-B48F-1D18A9856A87","last_name":"Barton"},{"last_name":"Tkačik","id":"3D494DCA-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0002-6699-1455","first_name":"Gašper","full_name":"Tkačik, Gašper"}],"alternative_title":["ISTA Thesis"],"title":"Genetic information and biological optimization","publisher":"Institute of Science and Technology Austria","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","date_published":"2024-02-23T00:00:00Z","oa_version":"Published Version","publication_status":"published","doi":"10.15479/at:ista:15020","citation":{"apa":"Hledik, M. (2024). <i>Genetic information and biological optimization</i>. Institute of Science and Technology Austria. <a href=\"https://doi.org/10.15479/at:ista:15020\">https://doi.org/10.15479/at:ista:15020</a>","ista":"Hledik M. 2024. Genetic information and biological optimization. Institute of Science and Technology Austria.","mla":"Hledik, Michal. <i>Genetic Information and Biological Optimization</i>. Institute of Science and Technology Austria, 2024, doi:<a href=\"https://doi.org/10.15479/at:ista:15020\">10.15479/at:ista:15020</a>.","chicago":"Hledik, Michal. “Genetic Information and Biological Optimization.” Institute of Science and Technology Austria, 2024. <a href=\"https://doi.org/10.15479/at:ista:15020\">https://doi.org/10.15479/at:ista:15020</a>.","short":"M. Hledik, Genetic Information and Biological Optimization, Institute of Science and Technology Austria, 2024.","ieee":"M. Hledik, “Genetic information and biological optimization,” Institute of Science and Technology Austria, 2024.","ama":"Hledik M. Genetic information and biological optimization. 2024. doi:<a href=\"https://doi.org/10.15479/at:ista:15020\">10.15479/at:ista:15020</a>"},"ddc":["576","519"],"file_date_updated":"2024-02-23T14:20:16Z","_id":"15020","acknowledged_ssus":[{"_id":"ScienComp"}],"year":"2024","date_updated":"2025-06-30T13:21:09Z","abstract":[{"text":"This thesis consists of four distinct pieces of work within theoretical biology, with two themes in common: the concept of optimization in biological systems, and the use of information-theoretic tools to quantify biological stochasticity and statistical uncertainty.\r\nChapter 2 develops a statistical framework for studying biological systems which we believe to be optimized for a particular utility function, such as retinal neurons conveying information about visual stimuli. We formalize such beliefs as maximum-entropy Bayesian priors, constrained by the expected utility. We explore how such priors aid inference of system parameters with limited data and enable optimality hypothesis testing: is the utility higher than by chance?\r\nChapter 3 examines the ultimate biological optimization process: evolution by natural selection. As some individuals survive and reproduce more successfully than others, populations evolve towards fitter genotypes and phenotypes. We formalize this as accumulation of genetic information, and use population genetics theory to study how much such information can be accumulated per generation and maintained in the face of random mutation and genetic drift. We identify the population size and fitness variance as the key quantities that control information accumulation and maintenance.\r\nChapter 4 reuses the concept of genetic information from Chapter 3, but from a different perspective: we ask how much genetic information organisms actually need, in particular in the context of gene regulation. For example, how much information is needed to bind transcription factors at correct locations within the genome? Population genetics provides us with a refined answer: with an increasing population size, populations achieve higher fitness by maintaining more genetic information. Moreover, regulatory parameters experience selection pressure to optimize the fitness-information trade-off, i.e. minimize the information needed for a given fitness. This provides an evolutionary derivation of the optimization priors introduced in Chapter 2.\r\nChapter 5 proves an upper bound on mutual information between a signal and a communication channel output (such as neural activity). Mutual information is an important utility measure for biological systems, but its practical use can be difficult due to the large dimensionality of many biological channels. Sometimes, a lower bound on mutual information is computed by replacing the high-dimensional channel outputs with decodes (signal estimates). Our result provides a corresponding upper bound, provided that the decodes are the maximum posterior estimates of the signal.","lang":"eng"}],"ec_funded":1,"month":"02","publication_identifier":{"issn":["2663 - 337X"]},"oa":1,"status":"public"},{"citation":{"short":"R. Grah, Gene Regulation across Scales – How Biophysical Constraints Shape Evolution, Institute of Science and Technology Austria, 2020.","ieee":"R. Grah, “Gene regulation across scales – how biophysical constraints shape evolution,” Institute of Science and Technology Austria, 2020.","ama":"Grah R. Gene regulation across scales – how biophysical constraints shape evolution. 2020. doi:<a href=\"https://doi.org/10.15479/AT:ISTA:8155\">10.15479/AT:ISTA:8155</a>","apa":"Grah, R. (2020). <i>Gene regulation across scales – how biophysical constraints shape evolution</i>. Institute of Science and Technology Austria. <a href=\"https://doi.org/10.15479/AT:ISTA:8155\">https://doi.org/10.15479/AT:ISTA:8155</a>","mla":"Grah, Rok. <i>Gene Regulation across Scales – How Biophysical Constraints Shape Evolution</i>. Institute of Science and Technology Austria, 2020, doi:<a href=\"https://doi.org/10.15479/AT:ISTA:8155\">10.15479/AT:ISTA:8155</a>.","ista":"Grah R. 2020. Gene regulation across scales – how biophysical constraints shape evolution. Institute of Science and Technology Austria.","chicago":"Grah, Rok. “Gene Regulation across Scales – How Biophysical Constraints Shape Evolution.” Institute of Science and Technology Austria, 2020. <a href=\"https://doi.org/10.15479/AT:ISTA:8155\">https://doi.org/10.15479/AT:ISTA:8155</a>."},"ddc":["530","570"],"file_date_updated":"2020-07-30T13:04:55Z","date_published":"2020-07-24T00:00:00Z","oa_version":"Published Version","doi":"10.15479/AT:ISTA:8155","publication_status":"published","month":"07","oa":1,"publication_identifier":{"issn":["2663-337X"]},"status":"public","_id":"8155","year":"2020","abstract":[{"lang":"eng","text":"In the thesis we focus on the interplay of the biophysics and evolution of gene regulation. We start by addressing how the type of prokaryotic gene regulation – activation and repression – affects spurious binding to DNA, also known as\r\ntranscriptional crosstalk. We propose that regulatory interference caused by excess regulatory proteins in the dense cellular medium – global crosstalk – could be a factor in determining which type of gene regulatory network is evolutionarily preferred. Next,we use a normative approach in eukaryotic gene regulation to describe minimal\r\nnon-equilibrium enhancer models that optimize so-called regulatory phenotypes. We find a class of models that differ from standard thermodynamic equilibrium models by a single parameter that notably increases the regulatory performance. Next chapter addresses the question of genotype-phenotype-fitness maps of higher dimensional phenotypes. We show that our biophysically realistic approach allows us to understand how the mechanisms of promoter function constrain genotypephenotype maps, and how they affect the evolutionary trajectories of promoters.\r\nIn the last chapter we ask whether the intrinsic instability of gene duplication and amplification provides a generic alternative to canonical gene regulation. Using mathematical modeling, we show that amplifications can tune gene expression in many environments, including those where transcription factor-based schemes are\r\nhard to evolve or maintain. "}],"date_updated":"2023-09-07T13:13:27Z","related_material":{"record":[{"id":"7675","status":"public","relation":"part_of_dissertation"},{"status":"public","relation":"part_of_dissertation","id":"7569"},{"relation":"part_of_dissertation","status":"public","id":"7652"}]},"article_processing_charge":"No","department":[{"_id":"CaGu"},{"_id":"GaTk"}],"language":[{"iso":"eng"}],"type":"dissertation","page":"310","date_created":"2020-07-23T09:51:28Z","has_accepted_license":"1","supervisor":[{"first_name":"Calin C","orcid":"0000-0001-6220-2052","last_name":"Guet","id":"47F8433E-F248-11E8-B48F-1D18A9856A87","full_name":"Guet, Calin C"},{"first_name":"Gašper","orcid":"0000-0002-6699-1455","last_name":"Tkačik","id":"3D494DCA-F248-11E8-B48F-1D18A9856A87","full_name":"Tkačik, Gašper"}],"degree_awarded":"PhD","alternative_title":["ISTA Thesis"],"title":"Gene regulation across scales – how biophysical constraints shape evolution","user_id":"c635000d-4b10-11ee-a964-aac5a93f6ac1","publisher":"Institute of Science and Technology Austria","file":[{"file_size":16638998,"success":1,"relation":"main_file","content_type":"application/pdf","access_level":"open_access","file_id":"8176","creator":"rgrah","date_created":"2020-07-27T12:00:07Z","date_updated":"2020-07-27T12:00:07Z","file_name":"Thesis_RokGrah_200727_convertedNew.pdf"},{"creator":"rgrah","file_id":"8177","access_level":"closed","file_name":"Thesis_new.zip","date_updated":"2020-07-30T13:04:55Z","date_created":"2020-07-27T12:02:23Z","content_type":"application/zip","relation":"main_file","file_size":347459978}],"author":[{"full_name":"Grah, Rok","orcid":"0000-0003-2539-3560","first_name":"Rok","last_name":"Grah","id":"483E70DE-F248-11E8-B48F-1D18A9856A87"}],"project":[{"_id":"267C84F4-B435-11E9-9278-68D0E5697425","name":"Biophysically realistic genotype-phenotype maps for regulatory networks"}],"day":"24","acknowledgement":"For the duration of his PhD, Rok was a recipient of a DOC fellowship of the Austrian Academy of Sciences."},{"article_processing_charge":"No","related_material":{"record":[{"id":"7673","relation":"part_of_dissertation","status":"public"},{"relation":"part_of_dissertation","status":"public","id":"8250"}]},"date_created":"2020-10-13T16:46:14Z","page":"271","has_accepted_license":"1","language":[{"iso":"eng"}],"department":[{"_id":"GaTk"}],"type":"dissertation","title":"Perturbations of protein synthesis: from antibiotics to genetics and physiology","publisher":"Institute of Science and Technology Austria","user_id":"c635000d-4b10-11ee-a964-aac5a93f6ac1","supervisor":[{"full_name":"Tkačik, Gašper","first_name":"Gašper","orcid":"0000-0002-6699-1455","id":"3D494DCA-F248-11E8-B48F-1D18A9856A87","last_name":"Tkačik"},{"full_name":"Bollenbach, Mark Tobias","orcid":"0000-0003-4398-476X","first_name":"Mark Tobias","id":"3E6DB97A-F248-11E8-B48F-1D18A9856A87","last_name":"Bollenbach"}],"degree_awarded":"PhD","alternative_title":["ISTA Thesis"],"day":"14","acknowledgement":"I thank Life Science Facilities for their continuous support with providing top-notch laboratory materials, keeping the devices humming, and coordinating the repairs and building of custom-designed laboratory equipment with the MIBA Machine shop.","file":[{"content_type":"application/pdf","relation":"main_file","embargo":"2021-10-06","file_size":52636162,"file_name":"kavcicB_thesis202009.pdf","date_updated":"2021-10-07T22:30:03Z","date_created":"2020-10-15T06:41:20Z","creator":"bkavcic","checksum":"d708ecd62b6fcc3bc1feb483b8dbe9eb","file_id":"8663","access_level":"open_access"},{"date_created":"2020-10-15T06:41:53Z","file_name":"2020b.zip","date_updated":"2021-10-07T22:30:03Z","access_level":"closed","creator":"bkavcic","checksum":"bb35f2352a04db19164da609f00501f3","file_id":"8664","file_size":321681247,"relation":"source_file","content_type":"application/zip","embargo_to":"open_access"}],"author":[{"full_name":"Kavcic, Bor","id":"350F91D2-F248-11E8-B48F-1D18A9856A87","last_name":"Kavcic","orcid":"0000-0001-6041-254X","first_name":"Bor"}],"ddc":["571","530","570"],"file_date_updated":"2021-10-07T22:30:03Z","citation":{"chicago":"Kavcic, Bor. “Perturbations of Protein Synthesis: From Antibiotics to Genetics and Physiology.” Institute of Science and Technology Austria, 2020. <a href=\"https://doi.org/10.15479/AT:ISTA:8657\">https://doi.org/10.15479/AT:ISTA:8657</a>.","ista":"Kavcic B. 2020. Perturbations of protein synthesis: from antibiotics to genetics and physiology. Institute of Science and Technology Austria.","apa":"Kavcic, B. (2020). <i>Perturbations of protein synthesis: from antibiotics to genetics and physiology</i>. Institute of Science and Technology Austria. <a href=\"https://doi.org/10.15479/AT:ISTA:8657\">https://doi.org/10.15479/AT:ISTA:8657</a>","mla":"Kavcic, Bor. <i>Perturbations of Protein Synthesis: From Antibiotics to Genetics and Physiology</i>. Institute of Science and Technology Austria, 2020, doi:<a href=\"https://doi.org/10.15479/AT:ISTA:8657\">10.15479/AT:ISTA:8657</a>.","short":"B. Kavcic, Perturbations of Protein Synthesis: From Antibiotics to Genetics and Physiology, Institute of Science and Technology Austria, 2020.","ama":"Kavcic B. Perturbations of protein synthesis: from antibiotics to genetics and physiology. 2020. doi:<a href=\"https://doi.org/10.15479/AT:ISTA:8657\">10.15479/AT:ISTA:8657</a>","ieee":"B. Kavcic, “Perturbations of protein synthesis: from antibiotics to genetics and physiology,” Institute of Science and Technology Austria, 2020."},"publication_status":"published","doi":"10.15479/AT:ISTA:8657","date_published":"2020-10-14T00:00:00Z","oa_version":"Published Version","publication_identifier":{"issn":["2663-337X"],"isbn":["978-3-99078-011-4"]},"oa":1,"status":"public","month":"10","year":"2020","date_updated":"2023-09-07T13:20:48Z","abstract":[{"lang":"eng","text":"Synthesis of proteins – translation – is a fundamental process of life. Quantitative studies anchor translation into the context of bacterial physiology and reveal several mathematical relationships, called “growth laws,” which capture physiological feedbacks between protein synthesis and cell growth. Growth laws describe the dependency of the ribosome abundance as a function of growth rate, which can change depending on the growth conditions. Perturbations of translation reveal that bacteria employ a compensatory strategy in which the reduced translation capability results in increased expression of the translation machinery.\r\nPerturbations of translation are achieved in various ways; clinically interesting is the application of translation-targeting antibiotics – translation inhibitors. The antibiotic effects on bacterial physiology are often poorly understood. Bacterial responses to two or more simultaneously applied antibiotics are even more puzzling. The combined antibiotic effect determines the type of drug interaction, which ranges from synergy (the effect is stronger than expected) to antagonism (the effect is weaker) and suppression (one of the drugs loses its potency).\r\nIn the first part of this work, we systematically measure the pairwise interaction network for translation inhibitors that interfere with different steps in translation. We find that the interactions are surprisingly diverse and tend to be more antagonistic. To explore the underlying mechanisms, we begin with a minimal biophysical model of combined antibiotic action. We base this model on the kinetics of antibiotic uptake and binding together with the physiological response described by the growth laws. The biophysical model explains some drug interactions, but not all; it specifically fails to predict suppression.\r\nIn the second part of this work, we hypothesize that elusive suppressive drug interactions result from the interplay between ribosomes halted in different stages of translation. To elucidate this putative mechanism of drug interactions between translation inhibitors, we generate translation bottlenecks genetically using in- ducible control of translation factors that regulate well-defined translation cycle steps. These perturbations accurately mimic antibiotic action and drug interactions, supporting that the interplay of different translation bottlenecks partially causes these interactions.\r\nWe extend this approach by varying two translation bottlenecks simultaneously. This approach reveals the suppression of translocation inhibition by inhibited translation. We rationalize this effect by modeling dense traffic of ribosomes that move on transcripts in a translation factor-mediated manner. This model predicts a dissolution of traffic jams caused by inhibited translocation when the density of ribosome traffic is reduced by lowered initiation. We base this model on the growth laws and quantitative relationships between different translation and growth parameters.\r\nIn the final part of this work, we describe a set of tools aimed at quantification of physiological and translation parameters. We further develop a simple model that directly connects the abundance of a translation factor with the growth rate, which allows us to extract physiological parameters describing initiation. We demonstrate the development of tools for measuring translation rate.\r\nThis thesis showcases how a combination of high-throughput growth rate mea- surements, genetics, and modeling can reveal mechanisms of drug interactions. Furthermore, by a gradual transition from combinations of antibiotics to precise genetic interventions, we demonstrated the equivalency between genetic and chemi- cal perturbations of translation. These findings tile the path for quantitative studies of antibiotic combinations and illustrate future approaches towards the quantitative description of translation."}],"_id":"8657","acknowledged_ssus":[{"_id":"LifeSc"},{"_id":"M-Shop"}]},{"month":"03","oa":1,"publication_identifier":{"issn":["2663-337X"]},"status":"public","_id":"6071","year":"2019","abstract":[{"lang":"eng","text":"Transcription factors, by binding to specific sequences on the DNA, control the precise spatio-temporal expression of genes inside a cell. However, this specificity is limited, leading to frequent incorrect binding of transcription factors that might have deleterious consequences on the cell. By constructing a biophysical model of TF-DNA binding in the context of gene regulation, I will first explore how regulatory constraints can strongly shape the distribution of a population in sequence space. Then, by directly linking this to a picture of multiple types of transcription factors performing their functions simultaneously inside the cell, I will explore the extent of regulatory crosstalk -- incorrect binding interactions between transcription factors and binding sites that lead to erroneous regulatory states -- and understand the constraints this places on the design of regulatory systems. I will then develop a generic theoretical framework to investigate the coevolution of multiple transcription factors and multiple binding sites, in the context of a gene regulatory network that performs a certain function. As a particular tractable version of this problem, I will consider the evolution of two transcription factors when they transmit upstream signals to downstream target genes. Specifically, I will describe the evolutionary steady states and the evolutionary pathways involved, along with their timescales, of a system that initially undergoes a transcription factor duplication event. To connect this important theoretical model to the prominent biological event of transcription factor duplication giving rise to paralogous families, I will then describe a bioinformatics analysis of C2H2 Zn-finger transcription factors, a major family in humans, and focus on the patterns of evolution that paralogs have undergone in their various protein domains in the recent past. "}],"date_updated":"2025-05-28T11:57:05Z","citation":{"chicago":"Prizak, Roshan. “Coevolution of Transcription Factors and Their Binding Sites in Sequence Space.” Institute of Science and Technology Austria, 2019. <a href=\"https://doi.org/10.15479/at:ista:th6071\">https://doi.org/10.15479/at:ista:th6071</a>.","mla":"Prizak, Roshan. <i>Coevolution of Transcription Factors and Their Binding Sites in Sequence Space</i>. Institute of Science and Technology Austria, 2019, doi:<a href=\"https://doi.org/10.15479/at:ista:th6071\">10.15479/at:ista:th6071</a>.","apa":"Prizak, R. (2019). <i>Coevolution of transcription factors and their binding sites in sequence space</i>. Institute of Science and Technology Austria. <a href=\"https://doi.org/10.15479/at:ista:th6071\">https://doi.org/10.15479/at:ista:th6071</a>","ista":"Prizak R. 2019. Coevolution of transcription factors and their binding sites in sequence space. Institute of Science and Technology Austria.","short":"R. Prizak, Coevolution of Transcription Factors and Their Binding Sites in Sequence Space, Institute of Science and Technology Austria, 2019.","ama":"Prizak R. Coevolution of transcription factors and their binding sites in sequence space. 2019. doi:<a href=\"https://doi.org/10.15479/at:ista:th6071\">10.15479/at:ista:th6071</a>","ieee":"R. Prizak, “Coevolution of transcription factors and their binding sites in sequence space,” Institute of Science and Technology Austria, 2019."},"ddc":["576"],"file_date_updated":"2020-07-14T12:47:18Z","date_published":"2019-03-11T00:00:00Z","oa_version":"Published Version","doi":"10.15479/at:ista:th6071","publication_status":"published","supervisor":[{"full_name":"Tkačik, Gašper","last_name":"Tkačik","id":"3D494DCA-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0002-6699-1455","first_name":"Gašper"}],"degree_awarded":"PhD","alternative_title":["ISTA Thesis"],"title":"Coevolution of transcription factors and their binding sites in sequence space","user_id":"c635000d-4b10-11ee-a964-aac5a93f6ac1","publisher":"Institute of Science and Technology Austria","file":[{"file_size":20995465,"relation":"main_file","content_type":"application/pdf","date_created":"2019-03-06T16:05:07Z","file_name":"Thesis_final_PDFA_RoshanPrizak.pdf","date_updated":"2020-07-14T12:47:18Z","access_level":"open_access","file_id":"6072","creator":"rprizak","checksum":"e60a72de35d270b31f1a23d50f224ec0"},{"content_type":"application/zip","relation":"source_file","file_size":85705272,"title":"Latex files","date_updated":"2020-07-14T12:47:18Z","file_name":"thesis_v2_merge.zip","date_created":"2019-03-06T16:09:39Z","file_id":"6073","checksum":"67c2630333d05ebafef5f018863a8465","creator":"rprizak","access_level":"closed"}],"author":[{"first_name":"Roshan","last_name":"Prizak","id":"4456104E-F248-11E8-B48F-1D18A9856A87","full_name":"Prizak, Roshan"}],"project":[{"_id":"254E9036-B435-11E9-9278-68D0E5697425","grant_number":"P28844-B27","name":"Biophysics of information processing in gene regulation","call_identifier":"FWF"}],"day":"11","related_material":{"record":[{"id":"1358","status":"public","relation":"part_of_dissertation"},{"relation":"part_of_dissertation","status":"public","id":"955"}]},"article_processing_charge":"No","department":[{"_id":"GaTk"},{"_id":"NiBa"}],"language":[{"iso":"eng"}],"type":"dissertation","page":"189","date_created":"2019-03-06T16:16:10Z","has_accepted_license":"1"},{"citation":{"ieee":"S. A. Cepeda Humerez, “Estimating information flow in single cells,” Institute of Science and Technology Austria, 2019.","ama":"Cepeda Humerez SA. Estimating information flow in single cells. 2019. doi:<a href=\"https://doi.org/10.15479/AT:ISTA:6473\">10.15479/AT:ISTA:6473</a>","short":"S.A. Cepeda Humerez, Estimating Information Flow in Single Cells, Institute of Science and Technology Austria, 2019.","mla":"Cepeda Humerez, Sarah A. <i>Estimating Information Flow in Single Cells</i>. Institute of Science and Technology Austria, 2019, doi:<a href=\"https://doi.org/10.15479/AT:ISTA:6473\">10.15479/AT:ISTA:6473</a>.","ista":"Cepeda Humerez SA. 2019. Estimating information flow in single cells. Institute of Science and Technology Austria.","apa":"Cepeda Humerez, S. A. (2019). <i>Estimating information flow in single cells</i>. Institute of Science and Technology Austria. <a href=\"https://doi.org/10.15479/AT:ISTA:6473\">https://doi.org/10.15479/AT:ISTA:6473</a>","chicago":"Cepeda Humerez, Sarah A. “Estimating Information Flow in Single Cells.” Institute of Science and Technology Austria, 2019. <a href=\"https://doi.org/10.15479/AT:ISTA:6473\">https://doi.org/10.15479/AT:ISTA:6473</a>."},"file_date_updated":"2020-07-14T12:47:31Z","ddc":["004"],"oa_version":"Published Version","date_published":"2019-05-23T00:00:00Z","publication_status":"published","doi":"10.15479/AT:ISTA:6473","month":"05","status":"public","oa":1,"publication_identifier":{"issn":["2663-337X"]},"_id":"6473","date_updated":"2025-05-28T11:57:00Z","abstract":[{"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. ","lang":"eng"}],"year":"2019","keyword":["Information estimation","Time-series","data analysis"],"related_material":{"record":[{"id":"6900","status":"public","relation":"dissertation_contains"},{"id":"281","status":"public","relation":"dissertation_contains"},{"status":"public","relation":"dissertation_contains","id":"2016"},{"id":"1576","relation":"dissertation_contains","status":"public"}]},"article_processing_charge":"No","type":"dissertation","language":[{"iso":"eng"}],"department":[{"_id":"GaTk"}],"has_accepted_license":"1","date_created":"2019-05-21T00:11:23Z","page":"135","alternative_title":["ISTA Thesis"],"degree_awarded":"PhD","supervisor":[{"full_name":"Tkačik, Gašper","orcid":"0000-0002-6699-1455","first_name":"Gašper","id":"3D494DCA-F248-11E8-B48F-1D18A9856A87","last_name":"Tkačik"}],"publisher":"Institute of Science and Technology Austria","user_id":"c635000d-4b10-11ee-a964-aac5a93f6ac1","title":"Estimating information flow in single cells","author":[{"full_name":"Cepeda Humerez, Sarah A","id":"3DEE19A4-F248-11E8-B48F-1D18A9856A87","last_name":"Cepeda Humerez","first_name":"Sarah A"}],"file":[{"file_size":23937464,"content_type":"application/zip","relation":"source_file","access_level":"closed","file_id":"6480","creator":"scepeda","checksum":"75f9184c1346e10a5de5f9cc7338309a","date_created":"2019-05-23T11:18:16Z","file_name":"Thesis_Cepeda.zip","date_updated":"2020-07-14T12:47:31Z"},{"content_type":"application/pdf","relation":"main_file","file_size":16646985,"file_name":"CepedaThesis.pdf","date_updated":"2020-07-14T12:47:31Z","date_created":"2019-05-23T11:18:13Z","creator":"scepeda","checksum":"afdc0633ddbd71d5b13550d7fb4f4454","file_id":"6481","access_level":"open_access"}],"day":"23","tmp":{"short":"CC BY (4.0)","image":"/images/cc_by.png","name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode"}},{"supervisor":[{"orcid":"0000-0002-6699-1455","first_name":"Gasper","id":"3D494DCA-F248-11E8-B48F-1D18A9856A87","last_name":"Tkacik","full_name":"Tkacik, Gasper"}],"alternative_title":["ISTA Thesis"],"degree_awarded":"PhD","title":"Studying the complexities of transcriptional regulation","user_id":"c635000d-4b10-11ee-a964-aac5a93f6ac1","publisher":"Institute of Science and Technology Austria","file":[{"checksum":"ec453918c3bf8e6f460fd1156ef7b493","creator":"dernst","file_id":"6815","access_level":"closed","file_name":"Thesis_Georg_Rieckh_w_signature_page.pdf","date_updated":"2019-08-13T11:46:25Z","date_created":"2019-08-13T11:46:25Z","relation":"main_file","content_type":"application/pdf","file_size":2614660},{"checksum":"51ae398166370d18fd22478b6365c4da","creator":"dernst","file_id":"8542","access_level":"open_access","date_updated":"2020-09-21T11:30:40Z","file_name":"Thesis_Georg_Rieckh.pdf","date_created":"2020-09-21T11:30:40Z","relation":"main_file","content_type":"application/pdf","success":1,"file_size":6096178}],"author":[{"full_name":"Rieckh, Georg","first_name":"Georg","id":"34DA8BD6-F248-11E8-B48F-1D18A9856A87","last_name":"Rieckh"}],"day":"01","article_processing_charge":"No","publist_id":"6232","department":[{"_id":"GaTk"}],"language":[{"iso":"eng"}],"type":"dissertation","date_created":"2018-12-11T11:50:18Z","page":"114","has_accepted_license":"1","month":"08","oa":1,"publication_identifier":{"issn":["2663-337X"]},"status":"public","_id":"1128","year":"2016","abstract":[{"lang":"eng","text":"The process of gene expression is central to the modern understanding of how cellular systems\r\nfunction. In this process, a special kind of regulatory proteins, called transcription factors,\r\nare important to determine how much protein is produced from a given gene. As biological\r\ninformation is transmitted from transcription factor concentration to mRNA levels to amounts of\r\nprotein, various sources of noise arise and pose limits to the fidelity of intracellular signaling.\r\nThis thesis concerns itself with several aspects of stochastic gene expression: (i) the mathematical\r\ndescription of complex promoters responsible for the stochastic production of biomolecules,\r\n(ii) fundamental limits to information processing the cell faces due to the interference from multiple\r\nfluctuating signals, (iii) how the presence of gene expression noise influences the evolution\r\nof regulatory sequences, (iv) and tools for the experimental study of origins and consequences\r\nof cell-cell heterogeneity, including an application to bacterial stress response systems."}],"date_updated":"2023-09-07T11:44:34Z","citation":{"ama":"Rieckh G. Studying the complexities of transcriptional regulation. 2016.","ieee":"G. Rieckh, “Studying the complexities of transcriptional regulation,” Institute of Science and Technology Austria, 2016.","short":"G. Rieckh, Studying the Complexities of Transcriptional Regulation, Institute of Science and Technology Austria, 2016.","ista":"Rieckh G. 2016. Studying the complexities of transcriptional regulation. Institute of Science and Technology Austria.","mla":"Rieckh, Georg. <i>Studying the Complexities of Transcriptional Regulation</i>. Institute of Science and Technology Austria, 2016.","apa":"Rieckh, G. (2016). <i>Studying the complexities of transcriptional regulation</i>. Institute of Science and Technology Austria.","chicago":"Rieckh, Georg. “Studying the Complexities of Transcriptional Regulation.” Institute of Science and Technology Austria, 2016."},"ddc":["570"],"file_date_updated":"2020-09-21T11:30:40Z","date_published":"2016-08-01T00:00:00Z","oa_version":"Published Version","publication_status":"published"}]