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Exploiting the information provided by the molecular noise of a biological process has proven to be valuable in extracting knowledge about the underlying kinetic parameters and sources of variability from single cell measurements. However,…

Quantitative Methods · Quantitative Biology 2013-08-30 Jakob Ruess , Andreas Milias-Argeitis , John Lygeros

Co-localization of networks of genes in the nucleus is thought to play an important role in determining gene expression patterns. Based upon experimental data, we built a dynamical model to test whether pure diffusion could account for the…

Molecular Networks · Quantitative Biology 2012-03-06 Jing Kang , Bing Xu , Ye Yao , Wei Lin , Conor Hennessy , Peter Fraser , Jianfeng Feng

Functions of chemical composition are complex and discrete in nature making it impossible to optimize them with gradient methods. Genetic algorithms, which do not use derivative information, are used to maximize the thermal conductivity of…

Materials Science · Physics 2018-01-30 Alexander Kerr , Kieran Mullen

The expression of one gene might be regulated by its corresponding protein, which is called autoregulation. Although gene regulation is a central topic in biology, autoregulation is much less studied. In general, it is extremely difficult…

Molecular Networks · Quantitative Biology 2023-03-31 Yue Wang , Siqi He

MicroRNA-mediated regulation of gene expression is characterised by some distinctive features that set it apart from unregulated and transcription factor-regulated gene expression. Recently, a mathematical model has been proposed to…

Quantitative Methods · Quantitative Biology 2012-10-19 Indrani Bose , Sayantari Ghosh

The apparent stability of population oscillations in ecological systems is a long-standing puzzle. A generic solution for this problem is suggested here. The stabilizing mechanism involves the combined effect of spatial migration,…

Populations and Evolution · Quantitative Biology 2007-05-23 Refael Abta , Marcelo Schiffer , Avishag Ben-Ishay , Nadav M. Shnerb

The time taken for gene expression varies not least because proteins vary in length considerably. This paper uses an abstract, tuneable Boolean regulatory network model to explore gene expression time variation. In particular, it is shown…

Biomolecules · Quantitative Biology 2016-03-16 Larry Bull

Neural oscillations are electrical activities of the brain measurable at different frequencies. This paper studies the interaction between the fast and slow processes in the brain. We recorded signals intracranially from the simple Wistar…

Neurons and Cognition · Quantitative Biology 2022-05-12 Evgeniia S. Sevasteeva , Sergei A. Plotnikov , Dmitry R. Belov

Allostery is a fundamental mechanism of protein regulation and is commonly interpreted as modulating enzymatic activity or product abundance. Here we show that this view is incomplete. Using a stochastic model of allosteric regulation…

Molecular Networks · Quantitative Biology 2026-01-08 Pedro Pessoa , Steve Pressé , S. Banu Ozkan

A general theoretical framework is put forth to organize and understand various observed phenomena and mathematical relationships in the field of molecular biology. By modeling each cell in eukaryotic organisms as a processor having a…

Other Quantitative Biology · Quantitative Biology 2013-12-18 Barry D. Jacobson

Noise in the expression of a gene produces fluctuations in the concentration of the gene product. These fluctuations can interfere with optimal function or can be exploited to generate beneficial diversity between cells; gene expression…

Molecular Networks · Quantitative Biology 2015-05-13 Namiko Mitarai , Ian B. Dodd , Michael T. Crooks , Kim Sneppen

The rules that specify how the information contained in DNA codes amino acids, is called "the genetic code". Using a simplified version of the Penna nodel, we are using computer simulations to investigate the importance of the genetic code…

Genomics · Quantitative Biology 2009-11-10 E. Gultepe , M. L. Kurnaz

The control of gene expression involves complex mechanisms that show large variation in design. For example, genes can be turned on either by the binding of an activator (positive control) or the unbinding of a repressor (negative control).…

Biomolecules · Quantitative Biology 2010-07-27 Guy Shinar , Erez Dekel , Tsvi Tlusty , Uri Alon

Stochastic simulation can make the molecular processes of cellular control more vivid than the traditional differential-equation approach by generating typical system histories instead of just statistical measures such as the mean and…

Subcellular Processes · Quantitative Biology 2018-09-18 Kevin Y. Chen , Daniel M. Zuckerman , Philip C. Nelson

Gene expression is a noisy process and several mechanisms, both transcriptional and posttranscriptional, can stabilize protein levels in cells. Much work has focused on the role of miRNAs, showing in particular that miRNA-mediated…

Molecular Networks · Quantitative Biology 2017-03-09 Araks Martirosyan , Andrea De Martino , Andrea Pagnani , Enzo Marinari

Coupling the control of expression stochasticity (noise) to the ability of expression change (plasticity) can alter gene function and influence adaptation. A number of factors, such as transcription re-initiation, strong chromatin…

Genomics · Quantitative Biology 2012-09-12 Djordje Bajić , Juan F. Poyatos

We present an encoding technique that reduces the effects of noise on quantum spin systems whose operation is driven by Hamiltonian evolution. This technique is widely applicable, being most relevant to the scenarios where there are…

Quantum Physics · Physics 2022-03-28 Catherine Keele , Alastair Kay

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

Motivated by the aim to find new medical strategies to suppress undesirable neural synchronization we study the control of oscillations in a system of inhibitory coupled noisy oscillators. Using dynamical properties of inhibition, we find…

Disordered Systems and Neural Networks · Physics 2009-05-27 C. J. Tessone , E. Ullner , A. A. Zaikin , J. Kurths , R. Toral

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
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