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Numerous transcription factors self-assemble into different order oligomeric species in a way that is actively regulated by the cell. Until now, no general functional role has been identified for this widespread process. Here we capture the…

Molecular Networks · Quantitative Biology 2011-05-26 Jose M. G. Vilar , Leonor Saiz

DNA is subject to large deformations in a wide range of biological processes. Two key examples illustrate how such deformations influence the readout of the genetic information: the sequestering of eukaryotic genes by nucleosomes, and DNA…

Biomolecules · Quantitative Biology 2015-11-10 Stephanie Johnson , Martin Lindén , Rob Phillips

One of the fundamental tasks in understanding genomics is the problem of predicting Transcription Factor Binding Sites (TFBSs). With more than hundreds of Transcription Factors (TFs) as labels, genomic-sequence based TFBS prediction is a…

Machine Learning · Computer Science 2017-11-13 Jack Lanchantin , Arshdeep Sekhon , Ritambhara Singh , Yanjun Qi

The biological function of protein assemblies was conventionally equated with a unique three-dimensional protein structure and protein-specific interactions. However, in the past 20 years it was found that some assemblies contain long…

Transcription factors are able to associate to their binding sites on DNA faster than the physical limit posed by diffusion. Such high association rates can be achieved by alternating between three-dimensional diffusion and one-dimensional…

Biomolecules · Quantitative Biology 2017-12-07 Massimo Cencini , Simone Pigolotti

A great part of the effort in the study of coarse grained models of transcription networks is directed to the analysis of their dynamical features. In this letter, we consider the \emph{equilibrium} properties of such systems, showing that…

Molecular Networks · Quantitative Biology 2007-05-23 M. Cosentino Lagomarsino , P. Jona , B. Bassetti

Transcription factors (TFs) play a vital role in the regulation of gene expression thereby making them critical to many cellular processes. In this study, we used graph machine learning methods to create a compendium of TF cascades using…

The molecular network in an organism consists of transcription/translation regulation, protein-protein interactions/modifications and a metabolic network, together forming a system that allows the cell to respond sensibly to the multiple…

Molecular Networks · Quantitative Biology 2007-05-23 Sandeep Krishna , Anna M. C. Andersson , Szabolcs Semsey , Kim Sneppen

Feed-forward loops (FFLs) are among the most ubiquitously found motifs of reaction networks in nature. However, little is known about their stochastic behavior and the variety of network phenotypes they can exhibit. In this study, we…

Molecular Networks · Quantitative Biology 2021-04-08 Anna Terebus , Farid Manuchehrfar , Youfang Cao , Jie Liang

In synthetic biology, gene regulatory circuits are often constructed by combining smaller circuit components. Connections between components are achieved by transcription factors acting on promoters. If the individual components behave as…

Molecular Networks · Quantitative Biology 2011-02-15 Kyung Hyuk Kim , Herbert M. Sauro

Cells receive a wide variety of cellular and environmental signals, which must be processed combinatorially to generate specific and timely genetic responses. We present here a theoretical study on the combinatorial control and integration…

Soft Condensed Matter · Physics 2007-05-23 Nicolas E. Buchler , Ulrich Gerland , Terence Hwa

Gene regulation is a complex process involving the role of several genomic elements which work in concert to drive spatio-temporal expression. The experimental characterization of gene regulatory elements is a very complex and…

Genomics · Quantitative Biology 2007-10-11 Arvind Rao , Alfred O. Hero , David J. States , James Douglas Engel

Gene Regulatory Networks (GRNs) consisting of combinations of transcription factors (TFs) and their cis promoters are assumed to be sufficient to direct the development of organisms. Mutations in GRNs are assumed to be the primary drivers…

Molecular Networks · Quantitative Biology 2015-08-17 Eric Werner

MicroRNAs (miRNAs) are endogenous 22-nucleotide RNAs, which suppress gene expression by selectively binding to the 3-noncoding region of specific message RNAs through base-pairing. Given the diversity and abundance of miRNA targets, miRNAs…

Molecular Networks · Quantitative Biology 2007-05-23 Qinghua Cui , Zhenbao Yu , Enrico O. Purisima , Edwin Wang

MicroRNAs are small non-coding nucleotide sequences that regulate target protein expression at post-transcriptional levels. Biogenesis of microRNA is a highly regulated multi-step pathway. Regulation of miRNA biogenesis can be caused…

Molecular Networks · Quantitative Biology 2020-02-03 Dimpal A Nyayanit , Chetan J Gadgil

Surviving in a diverse environment requires corresponding organism responses. At the cellular level, such adjustment relies on the transcription factors (TFs) which must rapidly find their target sequences amidst a vast amount of…

Quantitative Methods · Quantitative Biology 2009-11-13 Vahid Rezania , Jack Tuszynski , Michael Hendzel

We build a simple model for feedback systems involving small RNA (sRNA) molecules based on the iron metabolism system in the bacterium E. coli, and compare it with the corresponding system in H. pylori which uses purely transcriptional…

Molecular Networks · Quantitative Biology 2009-11-13 Namiko Mitarai , Anna M. C. Andersson , Sandeep Krishna , Szabolcs Semsey , Kim Sneppen

Networks of gene regulation govern morphogenesis, determine cell identity and regulate cell function. But we have little understanding, at the local level, of which logics are biologically preferred or even permitted. To solve this puzzle,…

Molecular Networks · Quantitative Biology 2022-09-02 Thomas M. A. Fink , Ryan Hannam

Recently, microRNAs (miRNAs) have emerged as central posttranscriptional regulators of gene expression. miRNAs regulate many key biological processes, including cell growth, death, development and differentiation. This discovery is…

Molecular Networks · Quantitative Biology 2007-12-24 Edwin Wang

Coregulation of the expression of groups of genes has been extensively demonstrated empirically in bacterial and eukaryotic systems. Such coregulation can arise through the use of shared regulatory motifs, which allow the coordinated…

Machine Learning · Statistics 2016-04-12 Jonathan H. Warrell , Musa M. Mhlanga
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