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The study of gene regulation and expression is often discussed in quantitative terms. In particular, the expression of genes is regularly characterized with respect to how much, how fast, when and where. Whether discussing the level of gene…

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

Deciphering how genes interpret information from the concentration of transcription factors (TFs) within the cell nucleus remains a fundamental question in gene regulation. Recent advancements have unveiled the heterogeneous distribution of…

Biological Physics · Physics 2024-11-07 Rahul Munshi , Jia Ling , Sergey Ryabichko , Eric F Wieschaus , Thomas Gregor

Genetic oscillators are present in the cells of many organisms and control several biological processes. The common feature of such oscillators is the presence of a protein which represses the transcription of its own gene. Recently, it has…

Molecular Networks · Quantitative Biology 2017-06-07 Nahuel Almeira , Sebastian Risau Gusman

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

Transcriptional regulatory network inference methods have been studied for years. Most of them relie on complex mathematical and algorithmic concepts, making them hard to adapt, re-implement or integrate with other methods. To address this…

Genomics · Quantitative Biology 2012-08-03 Jianlong Qi , Tom Michoel

This paper compares the auto-repressed gene to a simple one (a gene without auto-regulation) in terms of response time and output noise under the assumption of fixed metabolic cost. The analysis shows that, in the case of non-vanishing leak…

Molecular Networks · Quantitative Biology 2014-08-11 Nicolae Radu Zabet

We consider integrative modeling of multiple gene networks and diverse genomic data, including protein-DNA binding, gene expression and DNA sequence data, to accurately identify the regulatory target genes of a transcription factor (TF).…

Applications · Statistics 2012-03-21 Peng Wei , Wei Pan

Transcription Factors (TFs) are proteins that regulate gene expression. The regulation mechanism is via the binding of a TF to a specific part of the gene associated with it, the TF's target. The target of a specific TF corresponds to a…

Statistical Mechanics · Physics 2022-09-02 Ori Hachmo , Ariel Amir

Due to the stochastic nature of biochemical processes, the copy number of any given type of molecule inside a living cell often exhibits large temporal fluctuations. Here, we develop analytic methods to investigate how the noise arising…

Subcellular Processes · Quantitative Biology 2015-05-13 Li-ping Xiong , Yu-qiang Ma , Lei-Han Tang

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

We examine the binding of transcription factors to DNA in terms of an information transfer problem. The input of the noisy channel is the biophysical signal of a factor bound to a DNA site, and the output is a distribution of probable DNA…

Genomics · Quantitative Biology 2015-08-07 Yonatan Savir Jacob Kagan , Tsvi Tlusty

Multicellular organisms comprise a diverse collection of stable tissues built from different cell types. It remains unclear how large numbers of interacting cells can precisely coordinate their gene expression during tissue…

Biological Physics · Physics 2022-10-31 Matthew Smart , Anton Zilman

The precision of biochemical signaling is limited by randomness in the diffusive arrival of molecules at their targets. For proteins binding to the specific sites on the DNA and regulating transcription, the ability of the proteins to…

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

Cells integrate signals and make decisions about their future state in short amounts of time. A lot of theoretical effort has gone into asking how to best design gene regulatory circuits that fulfill a given function, yet little is known…

Molecular Networks · Quantitative Biology 2025-10-08 Tarek Tohme , Massimo Vergassola , Thierry Mora , Aleksandra M. Walczak

Stochasticity in gene expression can give rise to fluctuations in protein levels and lead to phenotypic variation across a population of genetically identical cells. Recent experiments indicate that bursting and feedback mechanisms play…

Molecular Networks · Quantitative Biology 2015-06-22 Niraj Kumar , Thierry Platini , Rahul V. Kulkarni

Eukaryotic gene regulation is based on stochastic yet controlled promoter switching, during which genes transition between transcriptionally active and inactive states. Despite the molecular complexity of this process, recent studies reveal…

Molecular Networks · Quantitative Biology 2025-07-17 Benjamin Zoller , Alexis Bénichou , Thomas Gregor , Gašper Tkačik

Information of relevance to the organism often is represented by the concentrations of particular molecules inside a cell. As outside observers we can now measure these concentrations precisely, but the cell's own mechanisms must be…

Biological Physics · Physics 2022-12-26 Marianne Bauer , William Bialek

Cells are often considered input-output devices that maximize the transmission of information by converting extracellular stimuli (input) via signaling pathways (communication channel) to cell behavior (output). However, in biological…

Cell Behavior · Quantitative Biology 2019-11-04 Gabriele Micali , Robert G. Endres

This paper is concerned with the problem of stochastic control of gene regulatory networks (GRNs) observed indirectly through noisy measurements and with uncertainty in the intervention inputs. The partial observability of the gene states…

Molecular Networks · Quantitative Biology 2017-02-27 Mahdi Imani , Ulisses Braga-Neto

Neurons in the central nervous system are affected by complex and noisy signals due to fluctuations in their cellular environment and in the inputs they receive from many other cells 1,2. Such noise usually increases the probability that a…

Neurons and Cognition · Quantitative Biology 2008-05-06 Boris S. Gutkin , Juergen Jost , Henry C. Tuckwell
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