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Stochasticity in gene expression gives rise to fluctuations in protein levels across a population of genetically identical cells. Such fluctuations can lead to phenotypic variation in clonal populations, hence there is considerable interest…

分子网络 · 定量生物学 2015-06-15 Hodjat Pendar , Thierry Platini , Rahul V. Kulkarni

This paper investigates the stochastic fluctuations of the number of copies of a given protein in a cell. This problem has already been addressed in the past and closed-form expressions of the mean and variance have been obtained for a…

定量方法 · 定量生物学 2012-06-05 Vincent Fromion , Emanuele Leoncini , Philippe Robert

Gene expression in individual cells is highly variable and sporadic, often resulting in the synthesis of mRNAs and proteins in bursts. Bursting in gene expression is known to impact cell-fate in diverse systems ranging from latency in HIV-1…

分子网络 · 定量生物学 2016-02-17 Niraj Kumar , Abhyudai Singh , Rahul V. Kulkarni

We introduce a biologically detailed, stochastic model of gene expression describing the multiple rate-limiting steps of transcription, nuclear pre-mRNA processing, nuclear mRNA export, cytoplasmic mRNA degradation and translation of mRNA…

分子网络 · 定量生物学 2024-01-24 Muhan Ma , Juraj Szavits-Nossan , Abhyudai Singh , Ramon Grima

We study a stochastic model of gene expression, in which protein production has a form of random bursts whose size distribution is arbitrary, whereas protein decay is a first-order reaction. We find exact analytical expressions for the time…

生物物理 · 物理学 2016-09-21 Jakub Jędrak , Anna Ochab-Marcinek

Gene expression is significantly stochastic making modeling of genetic networks challenging. We present an approximation that allows the calculation of not only the mean and variance but also the distribution of protein numbers. We assume…

分子网络 · 定量生物学 2008-12-18 Vahid Shahrezaei , Peter S. Swain

Stochastic modelling provides an indispensable tool for understanding how random events at the molecular level influence cellular functions. In practice, the common challenge is to calibrate a large number of model parameters against the…

分子网络 · 定量生物学 2015-03-17 Shuohao Liao , Tomas Vejchodsky , Radek Erban

Stochastic models of gene expression are typically formulated using the chemical master equation, which can be solved exactly or approximately using a repertoire of analytical methods. Here, we provide a tutorial review of an alternative…

亚细胞过程 · 定量生物学 2024-04-19 Juraj Szavits-Nossan , Ramon Grima

The Poisson distribution is the probability distribution of the number of independent events in a given period of time. Although the Poisson distribution appears ubiquitously in various stochastic dynamics of gene expression, both as…

统计力学 · 物理学 2024-10-02 Julian Lee

In this paper we analyze the equilibrium properties of a large class of stochastic processes describing the fundamental biological process within bacterial cells, {\em the production process of proteins}. Stochastic models classically used…

分子网络 · 定量生物学 2019-10-17 Philippe Robert

Understanding how stochastic gene expression is regulated in biological systems using snapshots of single-cell transcripts requires state-of-the-art methods of computational analysis and statistical inference. A Bayesian approach to…

定量方法 · 定量生物学 2018-12-10 Yen Ting Lin , Nicolas E. Buchler

Many of the existing stochastic models of gene expression contain the first-order decay reaction term that may describe active protein degradation or dilution. If the model variable is interpreted as the molecule number, and not…

生物物理 · 物理学 2019-05-22 Jakub Jędrak , Maciej Kwiatkowski , Anna Ochab-Marcinek

In this paper we develop a model of stochastic gene expression, which is an extension of the model investigated in the paper [T. Lipniacki, P. Paszek, A. Marciniak-Czochra, A.R. Brasier, M. Kimmel, Transcriptional stochasticity in gene…

概率论 · 数学 2015-10-20 Ryszard Rudnicki , Andrzej Tomski

Many fundamental cellular processes involve small numbers of molecules. When numbers are small, fluctuations dominate, and stochastic models, which account for these fluctuations, are required. In this chapter, we describe minimal…

分子网络 · 定量生物学 2015-10-05 Andrew Mugler , Sean Fancher

Gene transcription is a highly stochastic and dynamic process. As a result, the mRNA copy number of a given gene is heterogeneous both between cells and across time. We present a framework to model gene transcription in populations of cells…

定量方法 · 定量生物学 2017-01-10 Justine Dattani , Mauricio Barahona

Single-cell data reveal the presence of biological stochasticity between cells of identical genome and environment, in particular highlighting the transcriptional bursting phenomenon. To account for this property, gene expression may be…

分子网络 · 定量生物学 2026-05-19 Mathilde Gaillard , Ulysse Herbach

This paper considers adiabatic reduction in a model of stochastic gene expression with bursting transcription considered as a jump Markov process. In this model, the process of gene expression with auto-regulation is described by fast/slow…

概率论 · 数学 2013-01-14 Romain Yvinec , Changjing Zhuge , Jinzhi Lei , Michael C. Mackey

In this paper, we consider two stochastic models of gene expression in prokaryotic cells. In the first model, sixteen biochemical reactions involved in transcription, translation and transcriptional regulation in the presence of inducer…

凝聚态物理 · 物理学 2007-05-23 Indrani Bose , Rajesh Karmakar , Siddhartha Roy

In the last years, tens of thousands gene expression profiles for cells of several organisms have been monitored. Gene expression is a complex transcriptional process where mRNA molecules are translated into proteins, which control most of…

生物大分子 · 定量生物学 2009-11-11 T. Ochiai , J. C. Nacher , T. Akutsu

Gene expression is a stochastic process in which cells produce biomolecules essential to the function of life. Modern experimental methods allow for the measurement of biomolecules at single-cell and single-molecule resolution over time.…

定量方法 · 定量生物学 2022-07-01 Zachary R Fox
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