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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

The regulation of cellular function is often controlled at the level of gene transcription. Such genetic regulation usually consists of interacting networks, whereby gene products from a single network can act to control their own…

Biological Physics · Physics 2009-11-06 Jeff Hasty , Joel Pradines , Milos Dolnik , J. J. Collins

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

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

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

We present a study investigating the role of mitochondrial variability in generating noise in eukaryotic cells. Noise in cellular physiology plays an important role in many fundamental cellular processes, including transcription,…

Cell Behavior · Quantitative Biology 2015-05-28 Iain G. Johnston , Bernadett Gaal , Ricardo Pires das Neves , Tariq Enver , Francisco J. Iborra , Nick S. Jones

A central challenge in computational modeling of dynamic biological systems is parameter inference from experimental time course measurements. However, one would not only like to infer kinetic parameters but also study their variability…

Changes in a cell's external or internal conditions are usually reflected in the concentrations of the relevant transcription factors. These proteins in turn modulate the expression levels of the genes under their control and sometimes need…

Molecular Networks · Quantitative Biology 2013-08-01 Gasper Tkacik , Curtis G Callan , William Bialek

Even under constant external conditions, the expression levels of genes fluctuate. Much emphasis has been placed on the components of this noise that are due to randomness in transcription and translation; here we analyze the role of noise…

Molecular Networks · Quantitative Biology 2013-08-01 Gasper Tkacik , Thomas Gregor , William Bialek

Cellular decision making is based on regulatory circuits that associate signal thresholds to specific physiological actions. This transmission of information is subjected to molecular noise what can decrease its fidelity. Here, we show…

Molecular Networks · Quantitative Biology 2017-02-08 Guillermo Rodrigo , Juan F. Poyatos

The principle of maximum entropy is a broadly applicable technique for computing a distribution with the least amount of information possible constrained to match empirical data, for instance, feature expectations. We seek to generalize…

Information Theory · Computer Science 2022-05-30 Kenneth Bogert

It is well known that the kinetics of an intracellular biochemical network is stochastic. This is due to intrinsic noise arising from the random timing of biochemical reactions in the network as well as due to extrinsic noise stemming from…

Subcellular Processes · Quantitative Biology 2019-06-05 Emma M. Keizer , Bjorn Bastian , Robert W. Smith , Ramon Grima , Christian Fleck

Our understanding of cell division control in bacteria still relies largely on interpreting correlations between phenomenological variables, with limited connection to the underlying molecular mechanisms. Here, we analytically solve a…

Optimisation problems in science and engineering typically involve finding the ground state (i.e. the minimum energy configuration) of a cost function with respect to many variables. If the variables are corrupted by noise then this…

Quantum Physics · Physics 2016-03-08 Nicholas Chancellor , Szilard Szoke , Walter Vinci , Gabriel Aeppli , Paul A. Warburton

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

We derive exact solutions of simplified models for the temporal evolution of the protein concentration within a cell population arbitrarily far from the stationary state. We show that monitoring the dynamics can assist in modeling and…

Biomolecules · Quantitative Biology 2015-05-13 Sandro Azaele , Jayanth R. Banavar , Amos Maritan

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

After being considered as a nuisance to be filtered out, it became recently clear that biochemical noise plays a complex role, often fully functional, for a genetic network. The influence of intrinsic and extrinsic noises on genetic…

Molecular Networks · Quantitative Biology 2015-06-05 Giulio Caravagna , Giancarlo Mauri , Alberto d'Onofrio

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 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