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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…

分子网络 · 定量生物学 2016-09-13 Pavol Bokes , Abhyudai Singh

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…

分子网络 · 定量生物学 2011-03-02 Tao Jia , Rahul V. Kulkarni

Stochasticity in gene expression can give rise to fluctuations in protein levels and lead to phenotypic variation across a population of genetically identical cells. Recent experiments indicate that bursting and feedback mechanisms play…

分子网络 · 定量生物学 2015-06-22 Niraj Kumar , Thierry Platini , Rahul V. Kulkarni

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 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

In genetic circuits, when the mRNA lifetime is short compared to the cell cycle, proteins are produced in geometrically-distributed bursts, which greatly affects the cellular switching dynamics between different metastable phenotypic…

统计力学 · 物理学 2016-05-25 Shay Be'er , Metar Heller-Algazi , Michael Assaf

The inherent probabilistic nature of the biochemical reactions, and low copy number of species can lead to stochasticity in gene expression across identical cells. As a result, after induction of gene expression, the time at which a…

定量方法 · 定量生物学 2016-07-28 Khem Raj Ghusinga , Abhyudai Singh

An important occurrence in many cellular contexts is the crossing of a prescribed threshold by a regulatory protein. The timing of such events is stochastic as a consequence of the innate randomness in gene expression. A question of…

分子网络 · 定量生物学 2017-02-24 Khem Raj Ghusinga , Abhyudai Singh

The intrinsic stochasticity of gene expression can lead to large variability of protein levels across a population of cells. Variability (or noise) in protein distributions can be modulated by cellular mechanisms of gene regulation; in…

分子网络 · 定量生物学 2011-03-02 Tao Jia , Rahul V. Kulkarni

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…

分子网络 · 定量生物学 2021-10-12 Shigang Qiu , Tao Jia

A stochastic model of autoregulated bursty gene expression by Kumar et al. [Phys. Rev. Lett. 113, 268105 (2014)] has been exactly solved in steady-state conditions under the implicit assumption that protein numbers are sufficiently large…

亚细胞过程 · 定量生物学 2020-03-18 Chen Jia , Ramon Grima

This paper considers the behavior of discrete and continuous mathematical models for gene expression in the presence of transcriptional/translational bursting. We treat this problem in generality with respect to the distribution of the…

概率论 · 数学 2015-10-15 M. C. Mackey , M. Tyran-Kamińska , R. Yvinec

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…

分子网络 · 定量生物学 2017-02-24 Alma Dal Co , Marco Cosentino Lagomarsino , Michele Caselle , Matteo Osella

A key goal of systems biology is the predictive mathematical description of gene regulatory circuits. Different approaches are used such as deterministic and stochastic models, models that describe cell growth and division explicitly or…

分子网络 · 定量生物学 2012-10-12 Rahul Marathe , Veronika Bierbaum , David Gomez , Stefan Klumpp

Expression of many genes varies as a cell transitions through different cell-cycle stages. How coupling between stochastic expression and cell cycle impacts cell-to-cell variability (noise) in the level of protein is not well understood. We…

分子网络 · 定量生物学 2016-05-10 Mohammad Soltani , Abhyudai Singh

The intrinsic stochasticity of gene expression can lead to large variations in protein levels across a population of cells. To explain this variability, different sources of mRNA fluctuations ('Poisson' and 'Telegraph' processes) have been…

生物物理 · 物理学 2011-03-02 Vlad Elgart , Tao Jia , Rahul V. Kulkarni

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…

生物物理 · 物理学 2026-05-06 Yuntao Lu , Yunxin Zhang

Stochasticity in gene expression can result in fluctuations in gene product levels. Recent experiments indicated that feedback regulation plays an important role in controlling the noise in gene expression. A quantitative understanding of…

分子网络 · 定量生物学 2019-12-11 Zihao Wang , Zhenquan Zhang , Tianshou Zhou

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…

生物物理 · 物理学 2015-05-27 Vlad Elgart , Tao Jia , Andrew T. Fenley , Rahul V. Kulkarni

Intrinsic transcriptional noise induced by operator fluctuations is investigated with a simple spin like stochastic model. The effects of transcriptional fluctuations in protein synthesis is probed by coupling transcription and translation…

其他定量生物学 · 定量生物学 2007-05-23 Guilherme da C. P. Innocentini , Jose E. M. Hornos
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