English
Related papers

Related papers: Noise Processing by MicroRNA-Mediated Circuits: th…

200 papers

The telegraph model is the standard model of stochastic gene expression, which can be solved exactly to obtain the distribution of mature RNA numbers per cell. A modification of this model also leads to an analytical distribution of the…

Subcellular Processes · Quantitative Biology 2023-08-17 Juraj Szavits-Nossan , Ramon Grima

Here we investigate single-cell stochastic gene expression kinetics in a minimal coupled gene circuit with positive-plus-negative feedback. A triphasic stochastic bifurcation upon the increasing ratio of the positive and negative feedback…

Molecular Networks · Quantitative Biology 2019-11-27 Chen Jia , Le Yi Wang , George G. Yin , Michael Q. Zhang

A key goal of systems biology is the predictive mathematical description of gene regulatory circuits. Different approaches are used such as deterministic and stochastic models, models that describe cell growth and division explicitly or…

Molecular Networks · Quantitative Biology 2012-10-12 Rahul Marathe , Veronika Bierbaum , David Gomez , Stefan Klumpp

Chemical reactions in cell are subject to intense stochastic fluctuations. An important question is how the fundamental physiological behavior of cell is kept stable against those noisy perturbations. In this paper a stochastic model of…

Molecular Networks · Quantitative Biology 2009-11-13 Yurie Okabe , Masaki Sasai

Gene expression is inherently a noisy process which manifests as cell-to-cell variability in time evolution of proteins. Consequently, events that trigger at critical threshold levels of regulatory proteins exhibit stochasticity in their…

Subcellular Processes · Quantitative Biology 2016-09-26 Khem Raj Ghusinga , Abhyudai Singh

The observation that, through a titration mechanism, microRNAs (miRNAs) can act as mediators of effective interactions among their common targets (competing endogenous RNAs or ceRNAs) has brought forward the idea ('ceRNA hypothesis') that…

Molecular Networks · Quantitative Biology 2015-06-18 Matteo Figliuzzi , Andrea De Martino , Enzo Marinari

Gene transcription is a stochastic process that involves thousands of reactions. The first set of these reactions, which happen near a gene promoter, are considered to be the most important in the context of stochastic noise. The most…

Molecular Networks · Quantitative Biology 2022-02-01 Jaroslav Albert

Many transcription factors bind to DNA with a remarkable lack of specificity, so that regulatory binding sites compete with an enormous number of non-regulatory 'decoy' sites. For an auto-regulated gene, we show decoy sites decrease noise…

Molecular Networks · Quantitative Biology 2015-06-05 Anat Burger , Aleksandra M. Walczak , Peter G. Wolynes

We prove that nested canalizing functions are the minimum-sensitivity Boolean functions for any activity ratio and we determine the functional form of this boundary which has a nontrivial fractal structure. We further observe that the…

Molecular Networks · Quantitative Biology 2024-08-14 Hamza Coban

The recent development of single-cell transcriptomics has enabled gene expression to be measured in individual cells instead of being population-averaged. Despite this considerable precision improvement, inferring regulatory networks…

Molecular Networks · Quantitative Biology 2017-11-28 Ulysse Herbach , Arnaud Bonnaffoux , Thibault Espinasse , Olivier Gandrillon

Stochasticity is both exploited and controlled by cells. Although the intrinsic stochasticity inherent in biochemistry is relatively well understood, cellular variation, or 'noise', is predominantly generated by interactions of the system…

Molecular Networks · Quantitative Biology 2008-09-18 Vahid Shahrezaei , Julien F Ollivier , Peter S Swain

While noise is generally associated with uncertainties and often has a negative connotation in engineering, living organisms have evolved to adapt to (and even exploit) such uncertainty to ensure the survival of a species or implement…

Molecular Networks · Quantitative Biology 2022-09-29 Corentin Briat , Mustafa Khammash

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

Interactions between genes and gene products give rise to complex circuits that enable cells to process information and respond to external signals. Theoretical studies often describe these interactions using continuous, stochastic, or…

Molecular Networks · Quantitative Biology 2007-05-23 Madalena Chaves , Reka Albert , Eduardo D. Sontag

Noise caused by fluctuations at the molecular level is a fundamental part of intracellular processes. While the response of biological systems to noise has been studied extensively, there has been limited understanding of how to exploit it…

Molecular Networks · Quantitative Biology 2015-10-14 Daniel K. Wells , William L. Kath , Adilson E. Motter

A simple stochastic model of a self regulating gene that displays bistable switching is analyzed. While on, a gene transcribes mRNA at a constant rate. Transcription factors can bind to the DNA and affect the gene's transcription rate.…

Statistical Mechanics · Physics 2016-03-08 Jay Newby

Randomness is an unavoidable feature of the intracellular environment due to chemical reactants being present in low copy number. That phenomenon, predicted by Delbr\"uck long ago \cite{delbruck40}, has been detected in both prokaryotic…

Molecular Networks · Quantitative Biology 2013-02-11 Alexandre F. Ramos , Jose Eduardo M. Hornos , John Reinitz

Bursting cells lead to ambient RNA that contaminates sequencing data. This process is especially problematic in perturbation experiments where transcription factors are implanted into cells to determine their effects. The presence of…

Quantitative Methods · Quantitative Biology 2023-09-21 Forrest Sheldon

Robust machine learning for regulatory genomics is studied under biologically and technically induced distribution shifts. Deep convolutional and attention based models achieve strong in distribution performance on DNA regulatory sequence…

Genomics · Quantitative Biology 2026-02-20 Yiyao Yang

We study by simulation the effect of the diffusive motion of repressor molecules on the noise in mRNA and protein levels in the case of a repressed gene. We find that spatial fluctuations due to diffusion can drastically enhance the noise…

Molecular Networks · Quantitative Biology 2007-05-23 Jeroen S. van Zon , Marco J. Morelli , Sorin Tanase-Nicola , Pieter Rein ten Wolde
‹ Prev 1 4 5 6 7 8 10 Next ›