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The genetic repressilator circuit consists of three transcription factors, or repressors, which negatively regulate each other in a cyclic manner. This circuit was synthetically constructed on plasmids in {\it Escherichia coli} and was…

Molecular Networks · Quantitative Biology 2009-11-13 Adiel Loinger , Ofer Biham

The stochastic mutual repressor model is analysed using perturbation methods. This simple model of a gene circuit consists of two genes and three promotor states. Either of the two protein products can dimerize, forming a repressor molecule…

Biological Physics · Physics 2014-06-12 Jay Newby

Two synthetic gene circuits -- the genetic toggle switch and the repressilator -- are analyzed quantitatively and discussed in the context of an educational module on gene circuits and feedback that constitutes the final topic of a…

Physics Education · Physics 2015-06-16 S. B. Cahn , S. G. J. Mochrie

Biochemical reaction networks are subjected to large fluctuations attributable to small molecule numbers, yet underlie reliable biological functions. Most theoretical approaches describe them as purely deterministic or stochastic dynamical…

Molecular Networks · Quantitative Biology 2013-06-11 Jingkui Wang , Marc Lefranc , Quentin Thommen

We study the noise characteristics of stochastic oscillations in protein number dynamics of simple genetic oscillatory systems. Using the three-component negative feedback transcription regulatory system called the repressilator as a…

Molecular Networks · Quantitative Biology 2015-03-13 Byungjoon Min , K. -I. Goh , I. -M. Kim

Intrinsic transcriptional noise induced by operator fluctuations is investigated with a simple spin like stochastic model. The effects of transcriptional fluctuations in protein synthesis is probed by coupling transcription and translation…

Other Quantitative Biology · Quantitative Biology 2007-05-23 Guilherme da C. P. Innocentini , Jose E. M. Hornos

For cellular biochemical reaction systems where the numbers of molecules is small, significant noise is associated with chemical reaction events. This molecular noise can give rise to behavior that is very different from the predictions of…

Molecular Networks · Quantitative Biology 2009-11-13 Matthew Scott , Terence Hwa , Brian Ingalls

We describe an approach to model genetic regulatory networks at the level of promotion-inhibition circuitry through a class of stochastic spin models that includes spatial and temporal density fluctuations in a natural way. The formalism…

Statistical Mechanics · Physics 2018-03-08 J. Ricardo G. Mendonça , Mário J. de Oliveira

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

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

We present an approach for constructing dynamic models for the simulation of gene regulatory networks from simple computational elements. Each element is called a ``gene gate'' and defines an input/output-relationship corresponding to the…

Molecular Networks · Quantitative Biology 2007-10-09 R. Blossey , L. Cardelli , A. Phillips

The effects of intrinsic noise on stochastic delay systems is studied within an expansion in the inverse system size. We show that the stochastic nature of the underlying dynamics may induce oscillatory behaviour in parameter ranges where…

Molecular Networks · Quantitative Biology 2015-05-13 Tobias Galla

Gene Regulatory Networks(GRNs) with feedback are essential components of many cellular processes and may exhibit oscillatory behavior. Analyzing such systems becomes increasingly complex as the number of components increases. Since gene…

Molecular Networks · Quantitative Biology 2026-04-22 Manuel Eduardo Hernández-García , Jorge Velázquez-Castro

Understanding cell fate selection remains a central challenge in developmental biology. We present a class of simple yet biologically-motivated mathematical models for cell differentiation that generically generate oscillations and hence…

Dynamical Systems · Mathematics 2021-10-08 Saeed Farjami , Karen Camargo Sosa , Jonathan H. P. Dawes , Robert N. Kelsh , Andrea Rocco

Stochastic oscillations in individual cells are usually characterized by a non-monotonic power spectrum with an oscillatory autocorrelation function. Here we develop an analytical approach of stochastic oscillations in a minimal hybrid…

Molecular Networks · Quantitative Biology 2024-02-08 Chen Jia , Hong Qian , Michael Q. Zhang

Many fundamental cellular processes involve small numbers of molecules. When numbers are small, fluctuations dominate, and stochastic models, which account for these fluctuations, are required. In this chapter, we describe minimal…

Molecular Networks · Quantitative Biology 2015-10-05 Andrew Mugler , Sean Fancher

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

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

Gene expression has a stochastic component owing to the single molecule nature of the gene and the small number of copies of individual DNA binding proteins in the cell. We show how the statistics of such systems can be mapped on to quantum…

Disordered Systems and Neural Networks · Physics 2009-11-10 Masaki Sasai , Peter G. Wolynes

We introduce a biologically detailed, stochastic model of gene expression describing the multiple rate-limiting steps of transcription, nuclear pre-mRNA processing, nuclear mRNA export, cytoplasmic mRNA degradation and translation of mRNA…

Molecular Networks · Quantitative Biology 2024-01-24 Muhan Ma , Juraj Szavits-Nossan , Abhyudai Singh , Ramon Grima
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