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Related papers: Chemical models of genetic toggle switches

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We study genetic switches formed from pairs of mutually repressing operons. The switch stability is characterised by a well defined lifetime which grows sub-exponentially with the number of copies of the most-expressed transcription factor,…

Molecular Networks · Quantitative Biology 2009-11-10 Patrick B. Warren , Pieter Rein ten Wolde

Cells use genetic switches to shift between alternate gene expression states, e.g., to adapt to new environments or to follow a developmental pathway. Here, we study the dynamics of switching in a generic-feedback on/off switch. Unlike…

Molecular Networks · Quantitative Biology 2015-05-27 Michael Assaf , Elijah Roberts , Zaida Luthey-Schulten

We present a detailed analysis, based on the Forward Flux Sampling (FFS) simulation method, of the switching dynamics and stability of two models of genetic toggle switches, consisting of two mutually-repressing genes encoding transcription…

Molecular Networks · Quantitative Biology 2009-11-13 M. J. Morelli , S. Tanase-Nicola , R. J. Allen , P. R. ten Wolde

A toggle switch consists of two genes that mutually repress each other. This regulatory motif is active during cell differentiation and is thought to act as a memory device, being able to choose and maintain cell fate decisions. In this…

Molecular Networks · Quantitative Biology 2018-12-26 Michael K. Strasser , Fabian J. Theis , Carsten Marr

During tissue development, patterns of gene expression determine the spatial arrangement of cell types. In many cases, gradients of secreted signaling molecules - morphogens - guide this process. The continuous positional information…

Molecular Networks · Quantitative Biology 2017-02-08 Ruben Perez-Carrasco , Pilar Guerrero , James Briscoe , Karen Page

Genetic switch systems with mutual repression of two transcription factors are studied using deterministic methods (rate equations) and stochastic methods (the master equation and Monte Carlo simulations). These systems exhibit bistability,…

Molecular Networks · Quantitative Biology 2007-05-23 Adiel Loinger , Azi Lipshtat , Nathalie Q. Balaban , Ofer Biham

Stochastic dynamics of chemical reactions in a mutually repressing two-gene circuit is numerically simulated. The circuit has a rich variety of different states when the kinetic change of DNA status is slow. The stochastic switching…

Disordered Systems and Neural Networks · Physics 2009-11-11 Tomohiro Ushikubo , Wataru Inoue , Mitsumasa Yoda , Masaki Sasai

Homeostasis of protein concentrations in cells is crucial for their proper functioning, and this requires concentrations (at their steady-state levels) to be stable to fluctuations. Since gene expression is regulated by proteins such as…

Biological Physics · Physics 2020-11-10 Yipei Guo , Ariel Amir

Bistable biochemical switches are ubiquitous in gene regulatory networks and signal transduction pathways. Their switching dynamics, however, are difficult to study directly in experiments or conventional computer simulations, because…

Molecular Networks · Quantitative Biology 2009-11-10 Rosalind J. Allen , Patrick B. Warren , Pieter Rein ten Wolde

We present an analytical treatment of a genetic switch model consisting of two mutually inhibiting genes operating without cooperative binding of the corresponding transcription factors. Previous studies have numerically shown that these…

Molecular Networks · Quantitative Biology 2015-11-18 Tommaso Biancalani , Michael Assaf

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

We study the statistical properties of a simple genetic regulatory network that provides heterogeneity within a population of cells. This network consists of a binary genetic switch in which stochastic flipping between the two switch states…

Soft Condensed Matter · Physics 2009-03-31 Paolo Visco , Rosalind J. Allen , Martin R. Evans

We present a self-consistent field approximation to the problem of the genetic switch composed of two mutually repressing/activating genes. The protein and DNA state dynamics are treated stochastically and on equal footing. In this approach…

Molecular Networks · Quantitative Biology 2009-11-10 Aleksandra M. Walczak , Masaki Sasai , Peter G. Wolynes

We consider a generic class of gene circuits affected by nonlinear extrinsic noise. To address this nonlinearity we introduce a general perturbative methodology based on assuming timescale separation between noise and genes dynamics, with…

Molecular Networks · Quantitative Biology 2023-05-10 Gerardo Aquino , Andrea Rocco

Cells are known to utilize biochemical noise to probabilistically switch between distinct gene expression states. We demonstrate that such noise-driven switching is dominated by tails of probability distributions and is therefore…

Molecular Networks · Quantitative Biology 2009-11-13 Pankaj Mehta , Ranjan Mukhopadhyay , Ned S. Wingreen

It is well-known that gene activation/deactivation dynamics may be a major source of randomness in genetic networks, also in the case of large concentrations of the transcription factors. In this work, we investigate the effect of realistic…

Molecular Networks · Quantitative Biology 2014-10-28 Sebastiano de Franciscis , Giulio Caravagna , Alberto d'Onofrio

We use large deviation methods to calculate rates of noise-induced transitions between states in multistable genetic networks. We analyze a synthetic biochemical circuit, the toggle switch, and compare the results to those obtained from a…

Molecular Networks · Quantitative Biology 2013-05-29 David Marin Roma , Ruadhan A. O'Flanagan , Andrei E. Ruckenstein , Anirvan M. Sengupta , Ranjan Mukhopadhyay

Gene transcriptional regulatory is an inherently noisy process. In this paper, the study of fluctuations in a gene transcriptional regulatory system is extended to the case of L\'evy noise, a kind of non-Gaussian noises which can describe…

Biological Physics · Physics 2013-09-06 Yong Xu , Jing Feng , JuanJuan Li , Huiqing Zhang

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

In a stochastic process, noise often modifies the picture offered by the mean field dynamics. In particular, when there is an absorbing state, the noise erases a stable fixed point of the mean field equation from the stationary…

Statistical Mechanics · Physics 2018-12-19 JaeJun Lee , Julian Lee
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