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Characterization of pluripotent states, in which cells can both self-renew and differentiate, and the irreversible loss of pluripotency are important research areas in developmental biology. In particular, an understanding of these…

Molecular Networks · Quantitative Biology 2015-09-02 Tadashi Miyamoto , Chikara Furusawa , Kunihiko Kaneko

Statistical properties of environments experienced by biological signaling systems in the real world change, which necessitate adaptive responses to achieve high fidelity information transmission. One form of such adaptive response is gain…

Molecular Networks · Quantitative Biology 2012-05-01 Ilya Nemenman

DNA is subject to large deformations in a wide range of biological processes. Two key examples illustrate how such deformations influence the readout of the genetic information: the sequestering of eukaryotic genes by nucleosomes, and DNA…

Biomolecules · Quantitative Biology 2015-11-10 Stephanie Johnson , Martin Lindén , Rob Phillips

Oscillatory gene circuits are ubiquitous to biology and are involved in fundamental processes of cell cycle, circadian rhythms and developmental systems. The synthesis of small, non-natural oscillatory genetic circuits have been…

Molecular Networks · Quantitative Biology 2020-02-05 Yash Joshi , Yash Kiran Jawale , Chaitanya Anil Athale

Gene expression (GE) is an inherently random or stochastic or noisy process. The randomness in different steps of GE, e.g., transcription, translation, degradation, etc., leading to cell-to-cell variations in mRNA and protein levels. This…

Molecular Networks · Quantitative Biology 2021-01-12 Rajesh Karmakar , Amit Kumar Das

Regulation of gene expression is the consequence of interactions between the promoter of the gene and the transcription factors (TFs). In this paper, we explore the features of a genetic network where the TFs (activators and repressors)…

Molecular Networks · Quantitative Biology 2025-06-05 Amit Kumar Das , Debabrata Biswas

We analyze three simple genetic circuits which involve transcriptional regulation and feedback: the autorepressor, the switch and the repressilator, that consist of one, two and three genes, respectively. Such systems are commonly simulated…

Molecular Networks · Quantitative Biology 2007-05-23 Ofer Biham , Nathalie Q. Balaban , Adiel Loinger , Azi Lipshtat , Hagai B. Perets

A recurring motif in gene regulatory networks is transcription factors (TFs) that regulate each other, and then bind to overlapping sites on DNA, where they interact and synergistically control transcription of a target gene. Here, we…

Molecular Networks · Quantitative Biology 2013-03-07 Sahand Hormoz

Despite the greater functional importance of protein levels, our knowledge of gene expression evolution is based almost entirely on studies of mRNA levels. In contrast, our understanding of how translational regulation evolves has lagged…

Genomics · Quantitative Biology 2013-12-02 Carlo G. Artieri , Hunter B. Fraser

Recent whole genome polymerase binding assays have shown that a large proportion of unexpressed genes have pre-assembled RNA pol II transcription initiation complex stably bound to their promoters. Some such promoter proximally paused genes…

Molecular Networks · Quantitative Biology 2015-03-19 Alistair N. Boettiger , Peter L. Ralph , Steven N. Evans

A wealth of new research has highlighted the critical roles of small RNAs (sRNAs) in diverse processes such as quorum sensing and cellular responses to stress. The pathways controlling these processes often have a central motif comprising…

Molecular Networks · Quantitative Biology 2015-05-27 Charles Baker , Tao Jia , Rahul V. Kulkarni

We study the functional characteristics of a two-gene motif consisting of a double positive feedback loop and an autoregulatory negative feedback loop. The motif appears in the gene regulatory network controlling the functional activity of…

Molecular Networks · Quantitative Biology 2009-02-12 Subhasis Banerjee , Indrani Bose

In this paper we study the interplay between stochastic gene expression and system design using simple stochastic models of auto-activation and auto-inhibition. Using the Poisson Representation, a technique whose particular usefulness in…

Quantitative Methods · Quantitative Biology 2014-11-19 Srividya Iyer-Biswas , C. Jayaprakash

Protein synthesis rates are determined, at the translational level, by properties of the transcript's sequence. The efficiency of an mRNA can be tuned by varying the ribosome binding sites controlling the recruitment of the ribosomes, or…

Subcellular Processes · Quantitative Biology 2017-12-14 Lucas D. Fernandes , Alessandro P. S. de Moura , Luca Ciandrini

Cellular behavior is governed by gene regulatory processes that are intrinsically dynamic and nonlinear, and are subject to non-negligible amounts of random fluctuations. Such conditions are ubiquitous in physical systems, where they have…

Molecular Networks · Quantitative Biology 2011-09-21 Jordi Garcia-Ojalvo

Precise temporal coordination of gene expression is crucial for many developmental processes. One central question in developmental biology is how such coordinated expression patterns are robustly controlled. During embryonic development of…

Molecular Networks · Quantitative Biology 2015-05-14 Akihiko Nakajima , Takako Isshiki , Kunihiko Kaneko , Shuji Ishihara

The bistable gene regulatory switch controlling the transition from lysogeny to lysis in bacteriophage lambda presents a unique challenge to quantitative modeling. Despite extensive characterization of this regulatory network, the origin of…

Molecular Networks · Quantitative Biology 2015-05-13 Marco J. Morelli , Pieter Rein ten Wolde , Rosalind J. Allen

Generative probabilistic models have shown promise in designing artificial RNA and protein sequences but often suffer from high rates of false positives, where sequences predicted as functional fail experimental validation. To address this…

Biomolecules · Quantitative Biology 2025-04-03 Francesco Calvanese , Giovanni Peinetti , Polina Pavlinova , Philippe Nghe , Martin Weigt

Genetic switch systems with mutual repression of two transcription factors are studied using deterministic methods (rate equations) and stochastic methods (the master equation and Monte Carlo simulations). These systems exhibit bistability,…

Molecular Networks · Quantitative Biology 2007-05-23 Adiel Loinger , Azi Lipshtat , Nathalie Q. Balaban , Ofer Biham

Gene regulatory networks are collections of genes that interact with one other and with other substances in the cell. By measuring gene expression over time using high-throughput technologies, it may be possible to reverse engineer, or…

Applications · Statistics 2011-09-08 Andrea Rau , Florence Jaffrézic , Jean-Louis Foulley , R. W. Doerge