Biophysical Fitness Landscapes for Transcription Factor Binding Sites
نویسندگان
چکیده
منابع مشابه
Biophysical Fitness Landscapes for Transcription Factor Binding Sites
Phenotypic states and evolutionary trajectories available to cell populations are ultimately dictated by complex interactions among DNA, RNA, proteins, and other molecular species. Here we study how evolution of gene regulation in a single-cell eukaryote S. cerevisiae is affected by interactions between transcription factors (TFs) and their cognate DNA sites. Our study is informed by a comprehe...
متن کاملPseudocounts for transcription factor binding sites
To represent the sequence specificity of transcription factors, the position weight matrix (PWM) is widely used. In most cases, each element is defined as a log likelihood ratio of a base appearing at a certain position, which is estimated from a finite number of known binding sites. To avoid bias due to this small sample size, a certain numeric value, called a pseudocount, is usually allocated...
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We present a genomewide cross-species analysis of regulation for broad-acting transcription factors in yeast. Our model for binding site evolution is founded on biophysics: the binding energy between transcription factor and site is a quantitative phenotype of regulatory function, and selection is given by a fitness landscape that depends on this phenotype. The model quantifies conservation, as...
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The most important mechanism in the regulation of transcription is the binding of a transcription factor (TF) to a DNA sequence called the TF binding site (TFBS). Most binding sites are short and degenerate, which makes predictions based on their primary sequence alone somewhat unreliable. We present a new web tool that implements a flexible and extensible algorithm for predicting TFBS. The alg...
متن کاملEvolution of transcription factor DNA binding sites.
In bioinformatics, binding of transcription regulatory factors to the cognate binding sites is usually described by sequence-specific binding energy, which is estimated from a training sample of sites. This model implies that all binding sites with binding energy above some threshold are functional and site sequence variations should be considered neutral until they do not reduce this energy be...
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ژورنال
عنوان ژورنال: PLoS Computational Biology
سال: 2014
ISSN: 1553-7358
DOI: 10.1371/journal.pcbi.1003683