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Discrete-state stochastic models are a popular approach to describe the inherent stochasticity of gene expression in single cells. The analysis of such models is hindered by the fact that the underlying discrete state space is extremely…

Analysis of PDEs · Mathematics 2021-01-28 Pavel Kurasov , Delio Mugnolo , Verena Wolf

Phenotypical variability in the absence of genetic variation often reflects complex energetic landscapes associated with underlying gene regulatory networks (GRNs). In this view, different phenotypes are associated with alternative states…

Molecular Networks · Quantitative Biology 2018-06-27 M. Ali Al-Radhawi , Domitilla Del Vecchio , Eduardo D. Sontag

In many longitudinal microarray studies, the gene expression levels in a random sample are observed repeatedly over time under two or more conditions. The resulting time courses are generally very short, high-dimensional, and may have…

Applications · Statistics 2013-02-26 Maurice Berk , Cheryl Hemingway , Michael Levin , Giovanni Montana

Regulatory genes called small RNAs (sRNAs) are known to play critical roles in cellular responses to changing environments. For several sRNAs, regulation is effected by coupled stoichiometric degradation with messenger RNAs (mRNAs). The…

Biological Physics · Physics 2015-05-27 Thierry Platini , Tao Jia , Rahul V. Kulkarni

The production processes of proteins in prokaryotic cells are investigated. Most of the mathematical models in the literature study the production of {\em one} fixed type of proteins. When several classes of proteins are considered, an…

Quantitative Methods · Quantitative Biology 2014-11-07 Vincent Fromion , Emanuele Leoncini , Philippe Robert

Timing is essential for many cellular processes, from cellular responses to external stimuli to the cell cycle and circadian clocks. Many of these processes are based on gene expression. For example, an activated gene may be required to…

Molecular Networks · Quantitative Biology 2017-02-24 Alma Dal Co , Marco Cosentino Lagomarsino , Michele Caselle , Matteo Osella

We show how to construct a reduced description of interacting genes in noisy, small regulatory networks using coupled binary "spin" variables. Treating both the protein number and gene expression state variables stochastically and on equal…

Molecular Networks · Quantitative Biology 2015-05-13 Aleksandra M. Walczak , Peter G. Wolynes

Here we develop an effective approach to simplify two-time-scale Markov chains with infinite state spaces by removal of states with fast leaving rates, which improves the simplification method of finite Markov chains. We introduce the…

Molecular Networks · Quantitative Biology 2017-09-13 Chen Jia

Heterogeneity in gene expression across isogenic cell populations can give rise to phenotypic diversity, even when cells are in homogenous environments. This diversity arises from the discrete, stochastic nature of biochemical reactions,…

Quantitative Methods · Quantitative Biology 2017-08-31 Zachary Fox , Brian Munsky

Transcription factors (TFs) are key regulators of gene expression. Based on the classical scenario in which the TF search process switches between one-dimensional motion along the DNA molecule and free Brownian motion in the nucleus, we…

Genomics · Quantitative Biology 2010-10-15 Godefroy Malherbe , David Holcman

Single and collective cell migration are fundamental processes critical for physiological phenomena ranging from embryonic development and immune response to wound healing and cancer metastasis. To understand cell migration from a physical…

Biological Physics · Physics 2023-10-10 David B. Brückner , Chase P. Broedersz

Gene expression is a fundamental process in a living system. The small RNAs (sRNAs) is widely observed as a global regulator in gene expression. The inherent nonlinearity in this regulatory process together with the bursty production of…

Molecular Networks · Quantitative Biology 2021-10-12 Shigang Qiu , Tao Jia

We have developed a coarse-grained formulation for modeling the dynamic behavior of cells quantitatively, based on stochasticity and heterogeneity, rather than on biochemical reactions. We treat each reaction as a continuous-time stochastic…

Molecular Networks · Quantitative Biology 2015-05-28 Shunsuke Teraguchi , Yutaro Kumagai , Alexis Vandenbon , Shizuo Akira , Daron M Standley

Transcriptional pulsing has been observed in both prokaryotes and eukaryotes and plays a crucial role in cell to cell variability of protein and mRNA numbers. The issue is how the time constants associated with episodes of transcriptional…

Quantitative Methods · Quantitative Biology 2009-09-29 Srividya Iyer-Biswas , F. Hayot , C. Jayaprakash

We present an approach for constructing dynamic models for the simulation of gene regulatory networks from simple computational elements. Each element is called a ``gene gate'' and defines an input/output-relationship corresponding to the…

Molecular Networks · Quantitative Biology 2007-10-09 R. Blossey , L. Cardelli , A. Phillips

Toxicity evaluation of chemical compounds has traditionally relied on animal experiments;however, the demand for non-animal-based prediction methods for toxicology of compounds is increasing worldwide. Our aim was to provide a…

Applications · Statistics 2023-02-06 Jun-ichi Takeshita , Akinobu Toyoda , Hidenori Tani , Yasunori Endo , Sadaaki Miyamoto

Cell fate determination, the process through which cells commit to differentiated states is commonly mediated by gene regulatory motifs with mutually exclusive expression states. The classical deterministic picture for cell fate…

Molecular Networks · Quantitative Biology 2019-10-09 Manuel Pájaro , Irene Otero-Muras , Carlos Vázquez , Antonio A. Alonso

We analyst in detail a new approach to the monitoring and forecasting of the onset of transitions in high dimensional complex systems (see Phys. Rev. Lett . vol. 113, 264102 (2014)) by application to the Tangled Nature Model of evolutionary…

Adaptation and Self-Organizing Systems · Physics 2015-08-03 Duccio Piovani , Jelena Grujic , Henrik Jeldtoft Jensen

Feedback in cellular processes is typically inferred through cellular responses to experimental perturbations. Modular response analysis provides a theoretical framework for translating specific perturbations into feedback sensitivities…

Molecular Networks · Quantitative Biology 2025-05-09 Seshu Iyengar , Andreas Hilfinger

A widely used approach to describe the dynamics of gene regulatory networks is based on the chemical master equation, which considers probability distributions over all possible combinations of molecular counts. The analysis of such models…

Molecular Networks · Quantitative Biology 2019-06-04 Pavel Kurasov , Alexander Lück , Delio Mugnolo , Verena Wolf