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Due to the dynamic nature of biological systems, biological networks underlying temporal process such as the development of {\it Drosophila melanogaster} can exhibit significant topological changes to facilitate dynamic regulatory…

Molecular Networks · Quantitative Biology 2009-01-07 Amr Ahmed , Le Song , Eric P. Xing

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

We discuss two new approaches to extract relevant biological information on the Transcription Factors (and in particular to identify their binding sequences) from the statistical distribution of oligonucleotides in the upstream region of…

Biological Physics · Physics 2007-05-23 M. Caselle , F. Di Cunto , M. Pellegrino , P. Provero

Gene regulatory network inference uses genome-wide transcriptome measurements in response to genetic, environmental or dynamic perturbations to predict causal regulatory influences between genes. We hypothesized that evolution also acts as…

Genomics · Quantitative Biology 2015-05-20 Anagha Joshi , Yvonne Beck , Tom Michoel

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

Over the past few years, microRNAs (miRNAs) have emerged as a new prominent class of gene regulatory factors that negatively regulate expression of approximately one-third of the genes in animal genomes at post-transcriptional level.…

Genomics · Quantitative Biology 2007-05-23 Qinghua Cui , Zhenbao Yu , Youlian Pan , Enrico Purisima , Edwin Wang

Transcription factors (TFs) regulate gene expression through complex and co-operative mechanisms. While many TFs act together, the logic underlying TFs binding and their interactions is not fully understood yet. Most current approaches for…

Machine Learning · Computer Science 2026-03-13 Pietro Demurtas , Ferdinando Zanchetta , Giovanni Perini , Rita Fioresi

Segmentation in arthropod embryogenesis represents a well-known example of body plan diversity. Striped patterns of gene expression that lead to the future body segments appear simultaneously or sequentially in long and short germ-band…

Molecular Networks · Quantitative Biology 2008-07-31 Koichi Fujimoto , Shuji Ishihara , Kunihiko Kaneko

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

In the simplest view of transcriptional regulation, the expression of a gene is turned on or off by changes in the concentration of a transcription factor (TF). We use recent data on noise levels in gene expression to show that it should be…

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

The identification and validation of gene-gene interactions is a major challenge in human studies. Here, we explore an approach for studying epistasis in humans using a Drosophila melanogaster model of neonatal diabetes mellitus. Expression…

Recent genome-wide measurements of binding preferences of ~200 transcription regulators in the vicinity of transcription start sites in yeast, have provided a unique insight into the cis- regulatory code of a eukaryotic genome (Venters et…

Biomolecules · Quantitative Biology 2012-04-19 Ariel Afek , David B. Lukatsky

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

Genetic variation affecting gene regulation is a central driver of phenotypic differences between individuals and can be used to uncover how biological processes are organized in a cell. Although detecting cis-eQTLs is now routine,…

There is now a certain consensus that Transcription Factors (TFs) reach their target sites, where they regulate gene transcription, via a mechanism dubbed facilitated diffusion (FD). In FD, the TF cycles between events of 3D-diffusion in…

Biomolecules · Quantitative Biology 2015-06-18 Carlo Guardiani , Massimo Cencini , Fabio Cecconi

Precise temporal coordination of gene expression is crucial for many developmental processes. One central question in developmental biology is how such coordinated expression patterns are robustly controlled. During embryonic development of…

Molecular Networks · Quantitative Biology 2015-05-14 Akihiko Nakajima , Takako Isshiki , Kunihiko Kaneko , Shuji Ishihara

In this work, we describe a computational framework for the genome-wide identification and characterization of mixed transcriptional/post-transcriptional regulatory circuits in humans. We concentrated in particular on feed-forward loops…

Genomics · Quantitative Biology 2009-07-24 Angela Re , Davide Cora' , Daniela Taverna , Michele Caselle

Promoters and enhancers are cis-regulatory elements (CREs), DNA sequences that bind transcription factor (TF) proteins to up- or down-regulate target genes. Decades-long efforts yielded TF-DNA interaction models that predict how strongly an…

Populations and Evolution · Quantitative Biology 2026-01-30 Elia Mascolo , Réka Borbély , Noa Ottilie Borst , Nicholas H Barton , Justin Crocker , Gašper Tkačik

In many species, genomic data have revealed pervasive adaptive evolution indicated by the fixation of beneficial alleles. However, when selection pressures are highly variable along a species range or through time adaptive alleles may…

Populations and Evolution · Quantitative Biology 2014-11-10 Alan O. Bergland , Emily L. Behrman , Katherine R. O'Brien , Paul S. Schmidt , Dmitri A. Petrov

Synonymous sites are generally assumed to be subject to weak selective constraint. For this reason, they are often neglected as a possible source of important functional variation. We use site frequency spectra from deep population…

Populations and Evolution · Quantitative Biology 2013-06-14 David S. Lawrie , Philipp W. Messer , Ruth Hershberg , Dmitri A. Petrov