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Reliable in-silico design of synthetic gene networks necessitates novel approaches to model the process of protein synthesis under the influence of limited resources. We present such a novel protein synthesis model which originates from the…

Molecular Networks · Quantitative Biology 2016-10-14 Wolfgang Halter , Jan Maximilian Montenbruck , Zoltan A. Tuza , Frank Allgöwer

Evolutionary analyses of large populations commonly incorporate stochasticity through temporal variation in selection while treating genetic transmission as fixed. Much less attention has been given to stochasticity in transmission itself.…

Populations and Evolution · Quantitative Biology 2026-02-24 Elisa Heinrich-Mora , Marcus Feldman

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

mRNA-protein assemblies play a fundamental role in forming membraneless compartments within cells, whose functions may include activating, inhibiting, and localizing reactions. Recruitment of proteins into droplets can diminish cell to cell…

Subcellular Processes · Quantitative Biology 2025-11-14 Xinke Lyu , Alex Mayer , Grace McLaughlin , Amy Gladfelter , Marcus Roper

Small, non-coding RNAs (sRNAs) play important roles as genetic regulators in prokaryotes. sRNAs act post-transcriptionally via complementary pairing with target mRNAs to regulate protein expression. We use a quantitative approach to compare…

Molecular Networks · Quantitative Biology 2008-09-04 Pankaj Mehta , Sidhartha Goyal , Ned S. Wingreen

A common model of stochastic auto-regulatory gene expression describes promoter switching via cooperative protein binding, effective protein production in the active state and dilution of proteins. Here we consider an extension of this…

Subcellular Processes · Quantitative Biology 2020-04-07 James Holehouse , Abhishek Gupta , Ramon Grima

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…

Molecular Networks · Quantitative Biology 2015-06-22 Niraj Kumar , Thierry Platini , Rahul V. Kulkarni

This paper analyzes, in the context of a prokaryotic cell, the stochastic variability of the number of proteins when there is a control of gene expression by an autoregulation scheme. The goal of this work is to estimate the efficiency of…

Molecular Networks · Quantitative Biology 2016-07-15 Renaud Dessalles , Vincent Fromion , Philippe Robert

Eukaryotic transcription generally occurs in bursts of activity lasting minutes to hours; however, state-of-the-art measurements have revealed that many of the molecular processes that underlie bursting, such as transcription factor binding…

Subcellular Processes · Quantitative Biology 2020-12-21 Nicholas C. Lammers , Yang Joon Kim , Jiaxi Zhao , Hernan G. Garcia

In this paper, we study through mathematical modelling the combined effect of transcriptional and translational regulation by proteins and small noncoding RNAs (sRNA) in a genetic feedback motif that has an important role in the survival of…

Molecular Networks · Quantitative Biology 2018-02-16 Sutapa Mukherji

RNA binding proteins play a crucial role in post-transcriptional gene regulation by controlling the transport, processing, and translation of their target RNAs. Post-transcriptional gene regulation leads to the differential expression of…

Biomolecules · Quantitative Biology 2026-03-24 Danielle Wampler , Ralf Bundschuh

Replication of single-stranded RNA virus can be complicated, compared to that of double-stranded virus, as it require production of intermediate antigenomic strands that then serve as template for the genomic-sense strands. Moreover, for…

Dynamical Systems · Mathematics 2019-04-10 Leonid Shaikhet , Santiago F. Elena , Andrei Korobeinikov

Tight regulation of messenger RNA (mRNA) stability is essential to ensure accurate gene expression in response to developmental and environmental cues. mRNA stability is controlled by mRNA decay pathways, which have traditionally been…

Other Quantitative Biology · Quantitative Biology 2025-02-27 Jean-Marc Deragon , Rémy Merret

The number of substitutions (of nucleotides, amino acids, ...) that take place during the evolution of a sequence is a stochastic variable of fundamental importance in the field of molecular evolution. Although the mean number of…

Populations and Evolution · Quantitative Biology 2016-02-17 Bahram Houchmandzadeh , Marcel Vallade

Random matrix theory (RMT) is based on two assumptions: (1) matrix-element independence, and (2) base invariance. Most of the proposed generalizations keep the first assumption and violate the second. Recently, several authors presented…

Statistical Mechanics · Physics 2009-07-14 A. Y. Abul-Magd

A simple way to get insights about the possible functional motions of a protein is to perform a normal mode analysis (NMA). Indeed, it has been shown that low-frequency modes thus obtained are often closely related to domain motions…

Biomolecules · Quantitative Biology 2013-12-20 Yves-Henri Sanejouand

The observation that, through a titration mechanism, microRNAs (miRNAs) can act as mediators of effective interactions among their common targets (competing endogenous RNAs or ceRNAs) has brought forward the idea ('ceRNA hypothesis') that…

Molecular Networks · Quantitative Biology 2015-06-18 Matteo Figliuzzi , Andrea De Martino , Enzo Marinari

Gene transcription is a stochastic process that involves thousands of reactions. The first set of these reactions, which happen near a gene promoter, are considered to be the most important in the context of stochastic noise. The most…

Molecular Networks · Quantitative Biology 2022-02-01 Jaroslav Albert

Genes with similar transcriptional activation kinetics can display very different temporal mRNA profiles due to differences in transcription time, degradation rate and RNA processing kinetics. Recent studies have shown that a…

Gene expression (GE) is an inherently random or stochastic or noisy process. The randomness in different steps of GE, e.g., transcription, translation, degradation, etc., leading to cell-to-cell variations in mRNA and protein levels. This…

Molecular Networks · Quantitative Biology 2021-01-12 Rajesh Karmakar , Amit Kumar Das