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Related papers: On the bursting of gene products

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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…

Molecular Networks · Quantitative Biology 2016-02-17 Niraj Kumar , Abhyudai Singh , Rahul V. Kulkarni

This paper considers adiabatic reduction in both discrete and continuous models of stochastic gene expression. In gene expression models, the concept of bursting is a production of several molecules simultaneously and is generally…

Probability · Mathematics 2013-01-08 Romain Yvinec

The intrinsic stochasticity of gene expression can lead to large variability in protein levels for genetically identical cells. Such variability in protein levels can arise from infrequent synthesis of mRNAs which in turn give rise to…

Biological Physics · Physics 2015-05-27 Vlad Elgart , Tao Jia , Andrew T. Fenley , Rahul V. Kulkarni

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…

Molecular Networks · Quantitative Biology 2008-12-18 Vahid Shahrezaei , Peter S. Swain

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…

Biological Physics · Physics 2016-09-21 Jakub Jędrak , Anna Ochab-Marcinek

The burst approximation is a widely used technique to simplify stochastic gene expression models. However, the dynamics and analytical properties of the protein number distribution in gene expression models under the burst approximation are…

Biological Physics · Physics 2026-05-06 Yuntao Lu , Yunxin Zhang

Gene expression is inherently a noisy process which manifests as cell-to-cell variability in time evolution of proteins. Consequently, events that trigger at critical threshold levels of regulatory proteins exhibit stochasticity in their…

Subcellular Processes · Quantitative Biology 2016-09-26 Khem Raj Ghusinga , Abhyudai Singh

Stochastic modeling of gene expression is a classic problem in theoretical biophysics, and the burst approximation is widely used to simplify gene expression models formulated via the chemical master equation. However, the approximation…

Biological Physics · Physics 2026-03-31 Yuntao Lu , Yunxin Zhang

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…

Biological Physics · Physics 2019-05-22 Jakub Jędrak , Maciej Kwiatkowski , Anna Ochab-Marcinek

Recent experiments at the level of a single cell have shown that gene expression occurs in abrupt stochastic bursts. Further, in an ensemble of cells, the levels of proteins produced have a bimodal distribution. In a large fraction of…

Soft Condensed Matter · Physics 2009-11-07 Siddhartha Roy , Indrani Bose , Subhrangshu Sekhar Manna

The dynamics of short-lived mRNA results in bursts of protein production in gene regulatory networks. We investigate the propagation of bursting noise between different levels of mathematical modelling, and demonstrate that conventional…

Molecular Networks · Quantitative Biology 2016-01-14 Yen Ting Lin , Tobias Galla

The bulk of stochastic gene expression models in the literature do not have an explicit description of the age of a cell within a generation and hence they cannot capture events such as cell division and DNA replication. Instead, many…

Subcellular Processes · Quantitative Biology 2020-03-11 Casper H. L. Beentjes , Ruben Perez-Carrasco , Ramon Grima

Genetic oscillators are present in the cells of many organisms and control several biological processes. The common feature of such oscillators is the presence of a protein which represses the transcription of its own gene. Recently, it has…

Molecular Networks · Quantitative Biology 2017-06-07 Nahuel Almeira , Sebastian Risau Gusman

Systems biology approaches combining theoretical modeling with experiments have been singularly successful in uncovering novel features of cellular phenomena. One such feature is that of binary gene expression in which the expression level…

Subcellular Processes · Quantitative Biology 2012-07-31 Indrani Bose

Inside individual cells, expression of genes is stochastic across organisms ranging from bacterial to human cells. A ubiquitous feature of stochastic expression is burst-like synthesis of gene products, which drives considerable…

Molecular Networks · Quantitative Biology 2016-09-13 Pavol Bokes , Abhyudai Singh

We present a theoretical framework to analyze the dynamics of gene expression with stochastic bursts. Beginning with an individual-based model which fully accounts for the messenger RNA (mRNA) and protein populations, we propose a novel…

Molecular Networks · Quantitative Biology 2016-03-23 Yen Ting Lin , Charles R. Doering

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…

Probability · Mathematics 2013-01-14 Romain Yvinec , Changjing Zhuge , Jinzhi Lei , Michael C. Mackey

Recently, several theoretical and experimental studies have been undertaken to probe the effect of stochasticity on gene expression (GE). In experiments, the GE response to an inducing signal in a cell, measured by the amount of…

Other Quantitative Biology · Quantitative Biology 2009-11-10 Rajesh Karmakar , Indrani Bose

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

Regulation of intrinsic noise in gene expression is essential for many cellular functions. Correspondingly, there is considerable interest in understanding how different molecular mechanisms of gene expression impact variations in protein…

Molecular Networks · Quantitative Biology 2011-03-02 Tao Jia , Rahul V. Kulkarni
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