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A prominent feature of gene transcription regulatory networks is the presence in large numbers of motifs, i.e, patterns of interconnection, in the networks. One such motif is the feed forward loop (FFL) consisting of three genes X, Y and Z.…

Molecular Networks · Quantitative Biology 2009-11-10 Bhaswar Ghosh , Rajesh Karmakar , Indrani Bose

Predicting how genetic perturbations change cellular state is a core problem for building controllable models of gene regulation. Perturbations targeting the same gene can produce different transcriptional responses depending on their…

Genomics · Quantitative Biology 2026-02-12 Boyang Fu , George Dasoulas , Sameer Gabbita , Xiang Lin , Shanghua Gao , Xiaorui Su , Soumya Ghosh , Marinka Zitnik

Evolution of the spatial arrangement of cells in a primary culture of cardiac tissue derived from newborn rats was studied experimentally over extended period. It was found that cells attract each other spontaneously to form a clustered…

Cell Behavior · Quantitative Biology 2009-11-13 Takahiro Harada , Akihiro Isomura , Kenichi Yoshikawa

Timing is essential for many cellular processes, from cellular responses to external stimuli to the cell cycle and circadian clocks. Many of these processes are based on gene expression. For example, an activated gene may be required to…

Molecular Networks · Quantitative Biology 2017-02-24 Alma Dal Co , Marco Cosentino Lagomarsino , Michele Caselle , Matteo Osella

One goal of human genetics is to understand how the information for precise and dynamic gene expression programs is encoded in the genome. The interactions of transcription factors (TFs) with DNA regulatory elements clearly play an…

Genomics · Quantitative Biology 2014-04-15 Darren A. Cusanovich , Bryan Pavlovic , Jonathan K. Pritchard , Yoav Gilad

Riboswitches, structured elements in the untranslated regions of messenger RNAs, regulate gene expression by binding specific metabolites. We introduce a kinetic network model that describes the functions of riboswitches at the systems…

Molecular Networks · Quantitative Biology 2015-06-11 Jong-Chin Lin , D. Thirumalai

Eukaryotic DNA replication follows a specific temporal program, with some genomic regions consistently replicating earlier than others, yet what determines this program is largely unknown. Highly transcribed regions have been observed to…

Genomics · Quantitative Biology 2013-08-12 Hunter B. Fraser

Transforming growth factor beta (TGF$\beta$) plays a central role in morphogenesis, growth, and cell differentiation. This cytokine is particularly important in cartilage where it regulates cell proliferation and extracellular matrix…

Tissues and Organs · Quantitative Biology 2015-05-27 Catherine Baugé , Olivier Cauvard , Sylvain Leclercq , Philippe Galéra , Karim Boumédiene

Based on previously published experimental observations and mathematical models for Hes1, p53 and NF-kB gene expression, we improve these models through a distributed delay formulation of the time lag between transcription factor binding…

Molecular Networks · Quantitative Biology 2007-05-23 Katja Rateitschak , Olaf Wolkenhauer

We present a vector field method for obtaining the spatial organization of 3D patterns of gene expression based on gradients and lines of force obtained by numerical integration. The convergence of these lines of force in local maxima are…

Cellular differentiation is governed by gene regulatory networks, the high-dimensional stochastic biochemical systems that determine the transcriptional landscape and mediate cellular responses to signals and perturbations. Although…

Molecular Networks · Quantitative Biology 2026-04-29 Suryanarayana Maddu , Victor Chardès , Michael J. Shelley

Transforming Growth Factor-beta (TGF-beta) signalling is an important regulator of cellular growth and differentiation. The principal intracellular mediators of TGF-beta signalling are the Smad proteins, which upon TGF-beta stimulation…

Molecular Networks · Quantitative Biology 2007-05-23 D. C. Clarke , M. D. Betterton , X. Liu

Previous numerical investigations of an one-dimensional DNA model with an extended modified coupling constant by transcripting enzyme are integrated to longer time and demonstrated explicitly the trapping of breathers by DNA chains with…

solv-int · Physics 2021-01-21 Julian Juhi-Lian Ting

In 2000, Elowitz and Leibler introduced the repressilator--a synthetic gene circuit with three genes that cyclically repress transcription of the next gene--as well as a corresponding mathematical model. Experimental data and model…

Molecular Networks · Quantitative Biology 2019-01-01 Jonathan Tyler , Anne Shiu , Jay Walton

Finding out statistically significant words in DNA and protein sequences forms the basis for many genetic studies. By applying the maximal entropy principle, we give one systematic way to study the nonrandom occurrence of words in DNA or…

Biological Physics · Physics 2009-11-06 Rui Hu , Bin Wang

With the increasing amount of experimental data on gene expression and regulation, there is a growing need for quantitative models to describe the data and relate them to the different contexts. The thermodynamic models reviewed in the…

Molecular Networks · Quantitative Biology 2007-05-23 Lacramioara Bintu , Nicolas E. Buchler , Hernan G. Garcia , Ulrich Gerland , Terence Hwa , Jane' Kondev , Thomas Kuhlman , Rob Phillips

A proof is presented that gene regulatory networks (GRNs) based solely on transcription factors cannot control the development of complex multicellular life. GRNs alone cannot explain the evolution of multicellular life in the Cambrian…

Molecular Networks · Quantitative Biology 2014-01-28 Eric Werner

Recently, several studies have investigated the transcription process associated to specific genetic regulatory networks. In this work, we present a stochastic approach for analyzing the dynamics and effect of negative feedback loops (FBL)…

Molecular Networks · Quantitative Biology 2007-08-20 J. C. Nacher , T. Ochiai

We present a novel classification-based method for learning to predict gene regulatory response. Our approach is motivated by the hypothesis that in simple organisms such as Saccharomyces cerevisiae, we can learn a decision rule for…

Quantitative Methods · Quantitative Biology 2007-05-23 Manuel Middendorf , Anshul Kundaje , Chris Wiggins , Yoav Freund , Christina Leslie

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
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