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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…

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

Important cellular processes such as migration, differentiation, and development often rely on precise timing. Yet, the molecular machinery that regulates timing is inherently noisy. How do cells achieve precise timing with noisy…

Molecular Networks · Quantitative Biology 2018-07-04 Shivam Gupta , Julien Varennes , Hendrik C. Korswagen , Andrew Mugler

According to the `ceRNA hypothesis', microRNAs (miRNAs) may act as mediators of an effective positive interaction between long coding or non-coding RNA molecules, carrying significant potential implications for a variety of biological…

Molecular Networks · Quantitative Biology 2016-01-28 Araks Martirosyan , Matteo Figliuzzi , Enzo Marinari , Andrea De Martino

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

Using an analytically solvable stochastic model, we study the properties of a simple genetic circuit consisting of multiple copies of an self-regulating gene. We analyse how the variation in gene copy number and the mutations changing the…

Molecular Networks · Quantitative Biology 2016-08-17 Jakub Jędrak , Anna Ochab-Marcinek

Based on the measurements of noise in gene expression performed during the last decade, it has become customary to think of gene regulation in terms of a two-state model, where the promoter of a gene can stochastically switch between an ON…

Molecular Networks · Quantitative Biology 2015-06-16 Georg Rieckh , Gašper Tkačik

Cells are known to utilize biochemical noise to probabilistically switch between distinct gene expression states. We demonstrate that such noise-driven switching is dominated by tails of probability distributions and is therefore…

Molecular Networks · Quantitative Biology 2009-11-13 Pankaj Mehta , Ranjan Mukhopadhyay , Ned S. Wingreen

The dynamics of gene regulatory networks is governed by the interaction between deterministic biochemical reactions and molecular noise. To understand how gene regulatory networks process information during cell state transitions, we study…

Molecular Networks · Quantitative Biology 2025-09-11 Miguel Ángel García-Ariza , Alessandro Bravetti , Pablo Padilla , J Roberto Romero-Arias

Genetic regulatory networks enable cells to respond to the changes in internal and external conditions by dynamically coordinating their gene expression profiles. Our ability to make quantitative measurements in these biochemical circuits…

Biological Physics · Physics 2015-03-17 Aleksandra M Walczak , Gašper Tkačik

Populations of cells regulate gene expression in response to external signals, but their ability to make reliable collective decisions is limited by both intrinsic noise in molecular signaling and variability between individual cells. In…

Biological Physics · Physics 2026-03-20 Olivier Witteveen , Samuel J. Rosen , Ryan S. Lach , Maxwell Z. Wilson , Marianne Bauer

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

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

The inherent stochasticity of cellular processes leads to significant cell-to-cell variation in protein abundance. Although this noise has already been characterized and modeled, its broader implications and significance remain unclear. In…

Biological Physics · Physics 2023-07-10 Teresa W. Lo , Han Kyou James Choi , Dean Huang , Paul A. Wiggins

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…

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

We present a maximum entropy framework to separate intrinsic and extrinsic contributions to noisy gene expression solely from the profile of expression. We express the experimentally accessible probability distribution of the copy number of…

Subcellular Processes · Quantitative Biology 2015-06-12 Purushottam D. Dixit

Gene expression is a random or noisy process. The process consists of several random events among which the reinitiation of transcription by RNAP is an important one. The RNAP molecules can bind the gene only after the promoter gets…

Molecular Networks · Quantitative Biology 2020-08-26 Rajesh Karmakar

Noise in gene expression, either due to inherent stochasticity or to varying inter- and intracellular environment, can generate significant cell-to-cell variability of protein levels in clonal populations. We present a theoretical…

Other Quantitative Biology · Quantitative Biology 2010-04-08 Julia Rausenberger , Christian Fleck , Jens Timmer , Markus Kollmann

Transcription regulation is largely governed by the profile and the dynamics of transcription factors' binding to DNA. Stochastic effects are intrinsic to this dynamics and the binding to functional sites must be controled with a certain…

Genomics · Quantitative Biology 2007-05-23 Erik Aurell , Aymeric Fouquier d'Herouel , Claes Malmnas , Massimo Vergassola

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…

Other Quantitative Biology · Quantitative Biology 2007-05-23 Guilherme da C. P. Innocentini , Jose E. M. Hornos

It is well-known that gene activation/deactivation dynamics may be a major source of randomness in genetic networks, also in the case of large concentrations of the transcription factors. In this work, we investigate the effect of realistic…

Molecular Networks · Quantitative Biology 2014-10-28 Sebastiano de Franciscis , Giulio Caravagna , Alberto d'Onofrio