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The genetic repressilator circuit consists of three transcription factors, or repressors, which negatively regulate each other in a cyclic manner. This circuit was synthetically constructed on plasmids in {\it Escherichia coli} and was…

Molecular Networks · Quantitative Biology 2009-11-13 Adiel Loinger , Ofer Biham

Much of the complexity observed in gene regulation originates from cooperative protein-DNA binding. While studies of the target search of proteins for their specific binding sites on the DNA have revealed design principles for the…

Biomolecules · Quantitative Biology 2015-05-30 Nico Geisel , Ulrich Gerland

We consider a simplified model for gene regulation, where gene expression is regulated by transcription factors (TFs), which are single proteins or protein complexes. Proteins are in turn synthesised from expressed genes, creating a…

Molecular Networks · Quantitative Biology 2020-07-15 Giuseppe Torrisi , Reimer Kühn , Alessia Annibale

Gene regulatory circuits show significant stochastic fluctuations in their circuit signals due to the low copy number of transcription factors. When a gene circuit component is connected to an existing circuit, the dynamic properties of the…

Quantitative Methods · Quantitative Biology 2009-10-30 Kyung Hyuk Kim , Herbert M. Sauro

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

Transcriptional repression may cause transcriptional noise by a competition between repressor and RNA polymerase binding. Although promoter activity is often governed by a single limiting step, we argue here that the size of the noise…

Molecular Networks · Quantitative Biology 2015-08-14 Namiko Mitarai , Szabolcs Semsey , Kim Sneppen

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

The activation/repression of a given gene is typically regulated by multiple transcription factors (TFs) that bind at the gene regulatory region and recruit RNA polymerase (RNAP). The interactions between the promoter region and TFs and…

Molecular Networks · Quantitative Biology 2009-07-14 Herbert Sauro , Song Yang

Homeostasis of protein concentrations in cells is crucial for their proper functioning, and this requires concentrations (at their steady-state levels) to be stable to fluctuations. Since gene expression is regulated by proteins such as…

Biological Physics · Physics 2020-11-10 Yipei Guo , Ariel Amir

Many recent generative models make use of neural networks to transform the probability distribution of a simple low-dimensional noise process into the complex distribution of the data. This raises the question of whether biological networks…

Neural and Evolutionary Computing · Computer Science 2018-02-07 Hesham Mostafa , Gert Cauwenberghs

Competitive inhibitors can, paradoxically, stimulate an enzymatic reaction at low to moderate doses. Competitive inhibition of an enzyme occurs when an inhibitor binds to the enzyme's binding site and blocks the enzyme's target molecule…

Molecular Networks · Quantitative Biology 2025-09-09 Garrett Young , Mitchell Riley , Colleen Mitchell

For cellular biochemical reaction systems where the numbers of molecules is small, significant noise is associated with chemical reaction events. This molecular noise can give rise to behavior that is very different from the predictions of…

Molecular Networks · Quantitative Biology 2009-11-13 Matthew Scott , Terence Hwa , Brian Ingalls

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

Transcription factors are proteins that regulate gene activity by activating or repressing gene transcription. A special class of transcriptional repressors operates via a short-range mechanism, making local DNA regions inaccessible to…

Molecular Networks · Quantitative Biology 2022-04-13 F. E. Garbuzov , V. V. Gursky

Transcriptional regulatory network inference methods have been studied for years. Most of them relie on complex mathematical and algorithmic concepts, making them hard to adapt, re-implement or integrate with other methods. To address this…

Genomics · Quantitative Biology 2012-08-03 Jianlong Qi , Tom Michoel

In many organisms the expression levels of each gene are controlled by the activation levels of known "Transcription Factors" (TF). A problem of considerable interest is that of estimating the "Transcription Regulation Networks" (TRN)…

Applications · Statistics 2010-11-09 Gareth M. James , Chiara Sabatti , Nengfeng Zhou , Ji Zhu

A crucial step in the regulation of gene expression is binding of transcription factor (TF) proteins to regulatory sites along the DNA. But transcription factors act at nanomolar concentrations, and noise due to random arrival of these…

Molecular Networks · Quantitative Biology 2016-02-10 Thomas R. Sokolowski , Aleksandra M. Walczak , William Bialek , Gašper Tkačik

Gene regulation relies on the specificity of transcription factor (TF) - DNA interactions. In equilibrium, limited specificity may lead to crosstalk: a regulatory state in which a gene is either incorrectly activated due to noncognate…

Molecular Networks · Quantitative Biology 2016-10-31 Tamar Friedlander , Roshan Prizak , Călin C. Guet , Nicholas H. Barton , Gašper Tkačik

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

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