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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

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

We introduce a novel method to screen the promoters of a set of genes with shared biological function, against a precompiled library of motifs, and find those motifs which are statistically over-represented in the gene set. The gene sets…

Molecular Networks · Quantitative Biology 2008-11-11 Yuval Tabach , Ran Brosh , Yossi Buganim , Anat Reiner , Or Zuk , Assif Yitzhaky , Mark Koudritsky , Varda Rotter , Eytan Domany

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

An incoherent feed-forward loop (IFFL) is a network motif known for its ability to accelerate responses and generate pulses. Though functions of IFFLs are well studied, most previous computational analysis of IFFLs used ordinary…

Molecular Networks · Quantitative Biology 2020-09-29 Junmin Wang , Calin Belta , Samuel A. Isaacson

To regulate a particular gene, a transcription factor (TF) needs to bind a specific genome location. How is this genome address specified amid the presence of ~10^6-10^9 decoy sites? Our analysis of 319 known TF binding motifs clearly…

Genomics · Quantitative Biology 2009-01-21 Leonid A. Mirny , Zeba Wunderlich

Transcription factors (TFs) exert their regulatory action by binding to DNA with specific sequence preferences. However, different TFs can partially share their binding sequences due to their common evolutionary origin. This `redundancy' of…

Genomics · Quantitative Biology 2018-12-05 Antonio Rosanova , Alberto Colliva , Matteo Osella , Michele Caselle

Genes are connected in complex networks of interactions where often the product of one gene is a transcription factor that alters the expression of another. Many of these networks are based on a few fundamental motifs leading to switches…

Molecular Networks · Quantitative Biology 2026-03-05 Zitao Yang , Rebecca J. Rousseau , Sara D. Mahdavi , Hernan G. Garcia , Rob Phillips

We report a new mechanism for allelic dominance in regulatory genetic interactions that we call binding dominance. We investigated a biophysical model of gene regulation, where the fractional occupancy of a transcription factor (TF) on the…

Molecular Networks · Quantitative Biology 2016-08-30 Adam H. Porter , Norman A. Johnson , Alexander Y. Tulchinsky

Regulatory networks consist of interacting molecules with a high degree of mutual chemical specificity. How can these molecules evolve when their function depends on maintenance of interactions with cognate partners and simultaneous…

Populations and Evolution · Quantitative Biology 2017-11-01 Tamar Friedlander , Roshan Prizak , Nicholas H. Barton , Gašper Tkačik

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

Signal processing in biological systems is delicately executed by specialised networks, which are modular assemblies of network motifs. The motifs are independently functional circuits found in enormous numbers in any living cell. A very…

Molecular Networks · Quantitative Biology 2016-12-08 Tarunendu Mapder

Multi-sample microarray experiments have become a standard experimental method for studying biological systems. A frequent goal in such studies is to unravel the regulatory relationships between genes. During the last few years, regression…

Applications · Statistics 2008-12-18 Nancy R. Zhang , Mary C. Wildermuth , Terence P. Speed

Feed-forward dynamics, which is well-known to have several important implications in nonlinear dynamical systems, frequently occurs in gene expression motifs, and has been well explored experimentally and mathematically. However, dependency…

Molecular Networks · Quantitative Biology 2024-01-09 Priya Chakraborty , Ushasi Roy , Sayantari Ghosh

Often in bacterial regulatory networks, small noncoding RNAs (sRNA) interact with several mRNA species. The competition among mRNAs for binding to the same pool of sRNA might lead to crosstalk between the mRNAs. This is similar to the…

Molecular Networks · Quantitative Biology 2019-12-17 Swathi Tej , Sutapa Mukherji

Transcription factor binding sites vary in their specificity, both within and between species. Binding specificity has a strong impact on the evolution of gene expression, because it determines how easily regulatory interactions are gained…

Populations and Evolution · Quantitative Biology 2013-12-30 Alexander J. Stewart , Joshua B. Plotkin

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

Hill function is one of the widely used gene transcription regulation models. Its attribute of fitting may result in a lack of an underlying physical picture, yet the fitting parameters can provide information about biochemical reactions,…

Molecular Networks · Quantitative Biology 2024-03-05 Wenjia Shi , Yao Ma , Peilin Hu , Mi Pang , Xiaona Huang , Yiting Dang , Yuxin Xie , Danni Wu

The so-called Mixed Feedback Loop (MFL) is a small two-gene network where protein A regulates the transcription of protein B and the two proteins form a heterodimer. It has been found to be statistically over-represented in statistical…

Molecular Networks · Quantitative Biology 2009-11-11 Paul Francois , Vincent Hakim

Regulation of gene expression is the consequence of interactions between the promoter of the gene and the transcription factors (TFs). In this paper, we explore the features of a genetic network where the TFs (activators and repressors)…

Molecular Networks · Quantitative Biology 2025-06-05 Amit Kumar Das , Debabrata Biswas