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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

Gene expression is inherently noisy as many steps in the read-out of the genetic information are stochastic. To disentangle the effect of different sources of stochasticity in such systems, we consider various models that describe some…

Molecular Networks · Quantitative Biology 2015-06-05 Rahul Marathe , David Gomez , Stefan Klumpp

We show that noise-induced oscillations in a gene circuit model display stochastic coherence, that is, a maximum in the regularity of the oscillations as a function of noise amplitude. The effect is manifest as a system-size effect in a…

Molecular Networks · Quantitative Biology 2009-08-05 Robert C. Hilborn , Jessie D. Erwin

The influence of contrarians on the noisy voter model is studied at the mean-field level. The noisy voter model is a variant of the voter model where agents can adopt two opinions, optimistic or pessimistic, and can change them by means of…

Physics and Society · Physics 2018-10-10 Nagi Khalil , Raul Toral

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

Biological structure and function depend on complex regulatory interactions between many genes. A wealth of gene expression data is available from high-throughput genome-wide measurement technologies, but effective gene regulatory network…

Molecular Networks · Quantitative Biology 2016-03-28 Arwen Vanice Bradley , Ye Henry Li , Bokyung Choi , Wing Hung Wong

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

Filtered Poisson processes are often used as reference models for intermittent fluc- tuations in physical systems. Such a process is here extended by adding a noise term, either as a purely additive term to the process or as a dynamical…

Data Analysis, Statistics and Probability · Physics 2018-05-04 Audun Theodorsen , Odd Erik Garcia , Martin Rypdal

Neuronal membrane potentials fluctuate stochastically due to conductance changes caused by random transitions between the open and close states of ion channels. Although it has previously been shown that channel noise can nontrivially…

Neurons and Cognition · Quantitative Biology 2013-12-06 Brett A. Schmerl , Mark D. McDonnell

First return maps of interspike intervals for biological neurons that generate repetitive bursts of impulses can display stereotyped structures (neuronal signatures). Such structures have been linked to the possibility of multicoding and…

Neurons and Cognition · Quantitative Biology 2015-06-22 Bóris Marin , Reynaldo Daniel Pinto , Robert C Elson , Eduardo Colli

We study the synchronization behavior of a noisy network in which each system is driven by two sources of state-dependent noise: (1) an intrinsic noise which is common among all systems and can be generated by the environment or any…

Dynamical Systems · Mathematics 2021-03-09 Zahra Aminzare , Vaibhav Srivastava

Modeling stochasticity in gene regulatory networks is an important and complex problem in molecular systems biology. To elucidate intrinsic noise, several modeling strategies such as the Gillespie algorithm have been used successfully. This…

Molecular Networks · Quantitative Biology 2013-01-18 David Murrugarra , Alan Veliz-Cuba , Boris Aguilar , Seda Arat , Reinhard Laubenbacher

Gene expression and its regulation is a nonequilibrium stochastic process. Different molecules are involved in several biochemical steps in this process with low copies. It is observed that the stochasticity in biochemical processes is…

Molecular Networks · Quantitative Biology 2019-05-22 Rajesh Karmakar

In biochemical signaling, information is often encoded in oscillatory signals. However, the advantages of such a coding strategy over an amplitude encoding scheme of constant signals remain unclear. Here we study the dynamics of a simple…

Subcellular Processes · Quantitative Biology 2012-03-09 Filipe Tostevin , Wiet de Ronde , Pieter Rein ten Wolde

Transient properties of different physical systems with metastable states perturbed by external white noise have been investigated. Two noise-induced phenomena, namely the noise enhanced stability and the resonant activation, are…

Statistical Mechanics · Physics 2008-10-07 B. Spagnolo , A. A. Dubkov , A. L. Pankratov , E. V. Pankratova , A. Fiasconaro , A. Ochab-Marcinek

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

Fluctuations in intracellular reactions (intrinsic noise) reduce the information transmitted from an extracellular input to a cellular response. However, recent studies have demonstrated that the decrease in the transmitted information with…

Molecular Networks · Quantitative Biology 2019-10-09 Takehiro Tottori , Masashi Fujii , Shinya Kuroda

Understanding the relationship between spontaneous stochastic fluctuations and the topology of the underlying gene regulatory network is of fundamental importance for the study of single-cell stochastic gene expression. Here by solving the…

Molecular Networks · Quantitative Biology 2017-10-25 Chen Jia , Peng Xie , Min Chen , Michael Q. Zhang

We investigate the stabilization of unstable multidimensional partially observed single-sensor and multi-sensor linear systems driven by unbounded noise and controlled over discrete noiseless channels under fixed-rate information…

Optimization and Control · Mathematics 2012-09-21 Andrew P. Johnston , Serdar Yüksel

A central challenge in computational modeling of dynamic biological systems is parameter inference from experimental time course measurements. However, one would not only like to infer kinetic parameters but also study their variability…

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