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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

Gene regulatory networks are typically modeled using ordinary differential equations (ODEs) with phenomenological Hill functions to represent transcriptional regulation. While computationally efficient, Hill functions lack mechanistic…

Molecular Networks · Quantitative Biology 2026-01-16 Tianyu Wu

The Hill coefficient is often used as a direct measure of the cooperativity of binding processes. It is an essential tool for probing properties of reactions in many biochemical systems. Here we analyze existing experimental data and…

Biological Physics · Physics 2012-08-31 M. Sheinman , Y. Kafri

Quantitatively predicting phenotype variables by the expression changes in a set of candidate genes is of great interest in molecular biology but it is also a challenging task for several reasons. First, the collected biological…

Applications · Statistics 2017-07-21 Emilie Devijver , Mélina Gallopin , Emeline Perthame

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

We study the nonlinear dynamics of a completely inhomogeneous DNA chain which is governed by a perturbed sine-Gordon equation. A multiple scale perturbation analysis provides perturbed kink-antikink solitons to represent open state…

Pattern Formation and Solitons · Physics 2008-07-17 M. Daniel , V. Vasumathi

We develop a systems approach based on an energy-landscape concept to differentiate interactions involving redox activities and conformational changes of proteins and nucleic acids interactions in multi-layered protein-DNA regulatory…

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

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

Biological networks often encapsulate promotion/inhibition as signed edge-weights of a graph. Nodes may correspond to genes assigned expression levels (mass) of respective proteins. The promotion/inhibition nature of co-expression between…

Molecular Networks · Quantitative Biology 2023-08-21 Anqi Dong , Tryphon T. Georgiou , Allen Tannenbaum

Timely up- or down-regulation of gene expression is crucial for cellular differentiation and function. While gene upregulation via transcriptional activators has been extensively investigated, gene silencing remains understudied, especially…

Biological Physics · Physics 2025-09-15 Massimiliano Semeraro , Giuseppe Negro , Davide Marenduzzo , Giada Forte

Transcriptomic data is a treasure-trove in modern molecular biology, as it offers a comprehensive viewpoint into the intricate nuances of gene expression dynamics underlying biological systems. This genetic information must be utilised to…

Molecular Networks · Quantitative Biology 2023-12-13 Vikram Singh , Vikram Singh

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

The regulation of cellular function is often controlled at the level of gene transcription. Such genetic regulation usually consists of interacting networks, whereby gene products from a single network can act to control their own…

Biological Physics · Physics 2009-11-06 Jeff Hasty , Joel Pradines , Milos Dolnik , J. J. Collins

We used various analytical and numerical techniques to elucidate signal propagation in a small enzymatic cascade which is subjected to external and internal noise. The nonlinear character of catalytic reactions, which underlie protein…

Molecular Networks · Quantitative Biology 2009-11-13 Yueheng Lan , Garegin A. Papoian

The transcription factors, such as activators and repressors, can interact with the promoter of gene either in a competitive or non-competitive way. In this paper, we construct a stochastic model with non-competitive transcriptional…

Molecular Networks · Quantitative Biology 2022-05-27 Amit Kumar Das

We study the effects of multiple binding sites in the promoter of a genetic oscillator. We evaluate the regulatory function of a promoter with multiple binding sites in the absence of cooperative binding, and consider different hypotheses…

Adaptation and Self-Organizing Systems · Physics 2015-01-19 Iván M. Lengyel , Daniele Soroldoni , Andrew C. Oates , Luis G. Morelli

We revisit the dynamics of a gene repressed by its own protein in the case where the transcription rate does not adapt instantaneously to protein concentration but is a dynamical variable. We derive analytical criteria for the appearance of…

Quantitative Methods · Quantitative Biology 2009-02-19 Pierre-Emmanuel Morant , Quentin Thommen , François Lemaire , Constant Vandermoëre , Benjamin Parent , Marc Lefranc

Phenotypical variability in the absence of genetic variation often reflects complex energetic landscapes associated with underlying gene regulatory networks (GRNs). In this view, different phenotypes are associated with alternative states…

Molecular Networks · Quantitative Biology 2018-06-27 M. Ali Al-Radhawi , Domitilla Del Vecchio , Eduardo D. Sontag

The properties of certain networks are determined by hidden variables that are not explicitly measured. The conditional probability (propagator) that a vertex with a given value of the hidden variable is connected to k of other vertices…

Quantitative Methods · Quantitative Biology 2009-11-13 Gerald A. Miller , Yi Y. Shi , Hong Qian , Karol Bomsztyk
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