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Related papers: Dynamics of transcription factor binding site evol…

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Strong experimental and theoretical evidence shows that transcription factors and other specific DNA-binding proteins find their sites using a two-mode search: alternating between 3D diffusion through the cell and 1D sliding along the DNA.…

Biomolecules · Quantitative Biology 2008-06-11 Zeba Wunderlich , Leonid A. Mirny

Even under constant external conditions, the expression levels of genes fluctuate. Much emphasis has been placed on the components of this noise that are due to randomness in transcription and translation; here we analyze the role of noise…

Molecular Networks · Quantitative Biology 2013-08-01 Gasper Tkacik , Thomas Gregor , William Bialek

A blood cell lineage consists of several consecutive developmental stages from the pluri- or multipotent stem cell to a state of terminal differentiation. Despite their importance for human biology, the regulatory pathways and gene networks…

Molecular Networks · Quantitative Biology 2020-09-18 Maryam Nazarieh , Volkhard Helms , Marc P. Hoeppner , Andre Franke

In recent times whole-genome gene expression analysis has turned out to be a highly important tool to study the coordinated function of a very large number of genes within their corresponding cellular environment, especially in relation to…

Genomics · Quantitative Biology 2009-09-21 Enrique Hernandez-Lemus

We present a simple and efficient method for prediction of transcription factor binding sites from DNA sequence. Our method computes a random approximation of a convolutional kernel feature map from DNA sequence and then learns a linear…

Genomics · Quantitative Biology 2017-06-02 Alyssa Morrow , Vaishaal Shankar , Devin Petersohn , Anthony Joseph , Benjamin Recht , Nir Yosef

We study by mean-field analysis and stochastic simulations chemical models for genetic toggle switches formed from pairs of genes that mutually repress each other. In order to determine the stability of the genetic switches, we make a…

Molecular Networks · Quantitative Biology 2007-05-23 Patrick B. Warren , Pieter Rein ten Wolde

The binding of a transcription factor (TF) to a DNA operator site can initiate or repress the expression of a gene. Computational prediction of sites recognized by a TF has traditionally relied upon knowledge of several cognate sites,…

Biomolecules · Quantitative Biology 2008-11-10 Sahand Jamal Rahi , Peter Virnau , Leonid A. Mirny , Mehran Kardar

We describe the time evolution of gene expression levels by using a time translational matrix to predict future expression levels of genes based on their expression levels at some initial time. We deduce the time translational matrix for…

Statistical Mechanics · Physics 2009-11-07 Neal S. Holter , Amos Maritan , Marek Cieplak , Nina V. Fedoroff , Jayanth R. Banavar

Transcription factors (TFs) regulate gene expression by binding to specific genomic loci determined by DNA sequence. Their sequence specificity is commonly summarized by a consensus binding motif. However, eukaryotic genomes contain…

Transcriptional regulatory network inference methods have been studied for years. Most of them relie on complex mathematical and algorithmic concepts, making them hard to adapt, re-implement or integrate with other methods. To address this…

Genomics · Quantitative Biology 2012-08-03 Jianlong Qi , Tom Michoel

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

Gene regulation is a complex process involving the role of several genomic elements which work in concert to drive spatio-temporal expression. The experimental characterization of gene regulatory elements is a very complex and…

Genomics · Quantitative Biology 2007-10-11 Arvind Rao , Alfred O. Hero , David J. States , James Douglas Engel

Transcriptional and post-transcriptional regulation shape tissue-type-specific proteomes, but their relative contributions remain contested. Estimates of the factors determining protein levels in human tissues do not distinguish between (i)…

Genomics · Quantitative Biology 2017-05-15 Alexander Franks , Edoardo Airoldi , Nikolai Slavov

Through sequence-based classification, this paper tries to accurately predict the DNA binding sites of transcription factors (TFs) in an unannotated cellular context. Related methods in the literature fail to perform such predictions…

Machine Learning · Computer Science 2016-11-17 Ritambhara Singh , Jack Lanchantin , Gabriel Robins , Yanjun Qi

Quantitative understanding of the principles regulating nucleosome occupancy on a genome-wide level is a central issue in eukaryotic genomics. Here, we address this question using budding yeast, Saccharomyces cerevisiae, as a model…

Biomolecules · Quantitative Biology 2011-11-22 Ariel Afek , Itamar Sela , Noa Musa-Lempel , David B. Lukatsky

In subdivided populations, migration acts together with selection and genetic drift and determines their evolution. Building up on a recently proposed method, which hinges on the emergence of a time scale separation between local and global…

Populations and Evolution · Quantitative Biology 2015-03-24 Pierangelo Lombardo , Andrea Gambassi , Luca Dall'Asta

Specific activator and repressor transcription factors which bind to specific regulator DNA sequences, play an important role in gene activity control. Interactions between genes coding such transcription factors should explain the…

Dynamical Systems · Mathematics 2015-06-26 Gh. I. Mihalas , M. Neamtu , D. Opris , F. Horhat

One of the fundamental tasks in understanding genomics is the problem of predicting Transcription Factor Binding Sites (TFBSs). With more than hundreds of Transcription Factors (TFs) as labels, genomic-sequence based TFBS prediction is a…

Machine Learning · Computer Science 2017-11-13 Jack Lanchantin , Arshdeep Sekhon , Ritambhara Singh , Yanjun Qi

Over the past few years, microRNAs (miRNAs) have emerged as a new prominent class of gene regulatory factors that negatively regulate expression of approximately one-third of the genes in animal genomes at post-transcriptional level.…

Genomics · Quantitative Biology 2007-05-23 Qinghua Cui , Zhenbao Yu , Youlian Pan , Enrico Purisima , Edwin Wang

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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