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Some genes can promote or repress their own expressions, which is called autoregulation. Although gene regulation is a central topic in biology, autoregulation is much less studied. In general, it is extremely difficult to determine the…

分子网络 · 定量生物学 2022-08-30 Yue Wang , Siqi He

Expression of cellular genes is regulated by binding of transcription factors to their promoter, either activating or inhibiting transcription of a gene. Particularly interesting is the case when the expressed protein regulates its own…

分子网络 · 定量生物学 2016-11-28 Martin Jansen

This paper analyzes, in the context of a prokaryotic cell, the stochastic variability of the number of proteins when there is a control of gene expression by an autoregulation scheme. The goal of this work is to estimate the efficiency of…

分子网络 · 定量生物学 2016-07-15 Renaud Dessalles , Vincent Fromion , Philippe Robert

Using an analytically solvable stochastic model, we study the properties of a simple genetic circuit consisting of multiple copies of an self-regulating gene. We analyse how the variation in gene copy number and the mutations changing the…

分子网络 · 定量生物学 2016-08-17 Jakub Jędrak , Anna Ochab-Marcinek

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…

分子网络 · 定量生物学 2015-06-05 Rahul Marathe , David Gomez , Stefan Klumpp

A detailed stochastic model of single-gene auto-regulation is established and its solutions are explored when mRNA dynamics is fast compared with protein dynamics and in the opposite regime. The model includes all the sources of randomness…

生物物理 · 物理学 2015-06-03 Tomás Aquino , Elsa Abranches , Ana Nunes

Gene expression is a random or noisy process. The process consists of several random events among which the reinitiation of transcription by RNAP is an important one. The RNAP molecules can bind the gene only after the promoter gets…

分子网络 · 定量生物学 2020-08-26 Rajesh Karmakar

Living cells must control the reading out or "expression" of information encoded in their genomes, and this regulation often is mediated by transcription factors--proteins that bind to DNA and either enhance or repress the expression of…

分子网络 · 定量生物学 2013-08-01 Gašper Tkačik , Aleksandra M Walczak , William Bialek

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…

分子网络 · 定量生物学 2017-02-24 Alma Dal Co , Marco Cosentino Lagomarsino , Michele Caselle , Matteo Osella

From the response to external stimuli to cell division and death, the dynamics of living cells is based on the expression of specific genes at specific times. The decision when to express a gene is implemented by the binding and unbinding…

分子网络 · 定量生物学 2009-11-13 Johannes Berg

We investigate a conjecture used in recent experiments to reconstruct the complete dynamics of Fano autoionisation processes out of measured spectral amplitudes [Gruson et al, Science 354 734 (2016); Beaulieu el al, Science 358 1288 (2017);…

原子物理 · 物理学 2018-11-14 Antoine Desrier , Alfred Maquet , Richard Taïeb , Jérémie Caillat

We propose a methodology for the identification of transcription factors involved in the deregulation of genes in tumoral cells. This strategy is based on the inference of a reference gene regulatory network that connects transcription…

分子网络 · 定量生物学 2020-04-20 Magali Champion , Julien Chiquet , Pierre Neuvial , Mohamed Elati , François Radvanyi , Etienne Birmelé

The transcription factors, such as activators and repressors, can interact with the promoter of gene either in a competitive or non-competitive way. In this paper, we construct a stochastic model with non-competitive transcriptional…

分子网络 · 定量生物学 2022-05-27 Amit Kumar Das

Background: MicroRNAs, post-transcriptional repressors of gene expression, play a pivotal role in gene regulatory networks. They are involved in core cellular processes and their dysregulation is associated to a broad range of human…

分子网络 · 定量生物学 2012-06-13 Carla Bosia , Matteo Osella , Mariama El Baroudi , Davide Corà , Michele Caselle

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…

分子网络 · 定量生物学 2013-06-11 Jingkui Wang , Marc Lefranc , Quentin Thommen

In synthetic biology, gene regulatory circuits are often constructed by combining smaller circuit components. Connections between components are achieved by transcription factors acting on promoters. If the individual components behave as…

分子网络 · 定量生物学 2011-02-15 Kyung Hyuk Kim , Herbert M. Sauro

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…

定量方法 · 定量生物学 2012-10-19 Indrani Bose , Sayantari Ghosh

Gene expression is a central process to any form of life. It involves multiple temporal and functional scales that extend from specific protein-DNA interactions to the coordinated regulation of multiple genes in response to intracellular…

分子网络 · 定量生物学 2013-07-11 Jose M. G. Vilar , Leonor Saiz

Gene expression in response to stimuli is regulated by transcription factors (TFs) through feedback loop motifs, aimed at maintaining the desired TF concentration despite uncertainties and perturbations. In this work, we consider a…

适应与自组织系统 · 物理学 2026-02-19 Daniele Proverbio , Giulia Giordano

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…

分子网络 · 定量生物学 2016-03-28 Arwen Vanice Bradley , Ye Henry Li , Bokyung Choi , Wing Hung Wong
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