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Related papers: Predicting Growth Rate from Gene Expression

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In a letter published in Molecular Biology Evolution [10], Chen and Zhang argue that the variation of the mutation rate along the Escherichia coli genome that we recently reported [3] cannot be evolutionarily optimised. To support this…

Genomics · Quantitative Biology 2013-05-09 Inigo Martincorena , Nicholas M. Luscombe

We propose a biophysical model of Escherichia coli that predicts growth rate and an effective cellular composition from an effective, coarse-grained representation of its genome. We assume that E. coli is in a state of balanced exponential…

Molecular Networks · Quantitative Biology 2010-08-05 Arbel D. Tadmor , Tsvi Tlusty

Cell growth is determined by substrate availability and the cell's metabolic capacity to assimilate substrates into building blocks. Metabolic genes that determine growth rate may interact synergistically or antagonistically, and can…

Molecular Networks · Quantitative Biology 2019-01-17 Thomas P. Wytock , Aretha Fiebig , Jonathan W. Willett , Julien Herrou , Aleksandra Fergin , Adilson E. Motter , Sean Crosson

We present a novel classification-based method for learning to predict gene regulatory response. Our approach is motivated by the hypothesis that in simple organisms such as Saccharomyces cerevisiae, we can learn a decision rule for…

Quantitative Methods · Quantitative Biology 2007-05-23 Manuel Middendorf , Anshul Kundaje , Chris Wiggins , Yoav Freund , Christina Leslie

Biological cells replicate their genomes in a well-planned manner. The DNA replication program of an organism determines the timing at which different genomic regions are replicated, with fundamental consequences for cell homeostasis and…

Subcellular Processes · Quantitative Biology 2024-05-28 Florian Pflug , Deepak Bhat , Simone Pigolotti

One of the outstanding challenges in comparative genomics is to interpret the evolutionary importance of regulatory variation between species. Rigorous molecular evolution-based methods to infer evidence for natural selection from…

Populations and Evolution · Quantitative Biology 2013-10-16 Joshua G. Schraiber , Yulia Mostovoy , Tiffany Y. Hsu , Rachel B. Brem

Much recent work has explored molecular and population-genetic constraints on the rate of protein sequence evolution. The best predictor of evolutionary rate is expression level, for reasons which have remained unexplained. Here, we…

Populations and Evolution · Quantitative Biology 2007-05-23 D. Allan Drummond , Jesse D. Bloom , Christoph Adami , Claus O. Wilke , Frances H. Arnold

Protein interaction networks aim to summarize the complex interplay of proteins in an organism. Early studies suggested that the position of a protein in the network determines its evolutionary rate but there has been considerable…

Molecular Networks · Quantitative Biology 2007-05-23 Ino Agrafioti , Jonathan Swire , James Abbott , Derek Huntley , Sarah Butcher , Michael P. H. Stumpf

The variability in cell size of an isogenic population of Escherichia coli has been widely reported in experiment. The probability density function (PDF) of cell lengths has been variously described by exponential and lognormal functions.…

Cell Behavior · Quantitative Biology 2019-05-21 Chaitanya A. Athale

Isogenic Escherichia coli growing exponentially in a constant environment display large variation in growth-rates, division-sizes and generation-times. It is unclear how these seemingly random cell cycles can be reconciled with the precise…

Quantitative Methods · Quantitative Biology 2015-10-14 Mats Wallden , David Fange , Özden Baltekin , Johan Elf

Fluctuations in the measured mRNA levels of unperturbed cells under fixed conditions have often been viewed as an impediment to the extraction of information from expression profiles. Here, we argue that such expression fluctuations should…

Molecular Networks · Quantitative Biology 2007-05-23 William W. Chen , Jeremy L. England , Eugene I. Shakhnovich

A major challenge in synthetic genetic circuit development is the inter-dependency between heterologous gene expressions by circuits and host's growth rate. Increasing heterologous gene expression increases burden to the host, resulting in…

Molecular Networks · Quantitative Biology 2023-02-21 Huijuan Wang , Maurice HT Ling , Tze Kwang Chua , Chueh Loo Poh

The identification of cellular objectives is one of the central topics in the research of microbial metabolic networks. In particular, the information about a cellular objective is needed in flux balance analysis which is a commonly used…

Molecular Networks · Quantitative Biology 2012-03-22 Tommi Aho , Juha Kesseli , Olli Yli-Harja , Stuart A. Kauffman

A gene's rate of sequence evolution is among the most fundamental evolutionary quantities in common use, but what determines evolutionary rates has remained unclear. Here, we show that the two most commonly used methods to disentangle the…

Populations and Evolution · Quantitative Biology 2007-05-23 D. Allan Drummond , Alpan Raval , Claus O. Wilke

Establishing a quantitative connection between the population growth rate and the generation times of single cells is a prerequisite for understanding evolutionary dynamics of microbes. However, existing theories fail to account for the…

Populations and Evolution · Quantitative Biology 2017-09-19 Jie Lin , Ariel Amir

We model the growth of a cell population by a piecewise deterministic Markov branching tree. Each cell splits into two offsprings at a division rate $B(x)$ that depends on its size $x$. The size of each cell grows exponentially in time, at…

Probability · Mathematics 2015-05-29 Marie Doumic , Marc Hoffmann , Nathalie Krell , Lydia Robert

Cells adapt to different conditions by altering a vast number of components, which is measurable using transcriptome analysis. Given that a cell undergoing steady growth is constrained to sustain each of its internal components, the…

Cell Behavior · Quantitative Biology 2014-07-15 Kunihiko Kaneko , Chikara Furusawa , Tetsuya Yomo

In this paper we develop and test algorithmic techniques to estimate genotypes fitnesses by analysis of observed daily frequency data monitoring the long-term evolution of bacterial populations. In particular, we develop a non-linear least…

Populations and Evolution · Quantitative Biology 2020-10-05 Sergey S. Sarkisov , Ilya Timofeyev , Robert Azencott

Experiments in recent years have vividly demonstrated that gene expression can be highly stochastic. How protein concentration fluctuations affect the growth rate of a population of cells, is, however, a wide open question. We present a…

Molecular Networks · Quantitative Biology 2015-05-13 Sorin Tanase-Nicola , Pieter Rein ten Wolde

We consider evolution of a large population, where fitness of each organism is defined by many phenotypical traits. These traits result from expression of many genes. We propose a new model of gene regulation, where gene expression is…

Populations and Evolution · Quantitative Biology 2016-09-29 John Reinitz , Sergey Vakulenko , Dmitri Grigoriev , Andreas Weber
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