BayesPI-BAR: a new biophysical model for characterization of regulatory sequence variations.

ABSTRACT: Sequence variations in regulatory DNA regions are known to cause functionally important consequences for gene expression. DNA sequence variations may have an essential role in determining phenotypes and may be linked to disease; however, their identification through analysis of massive genome-wide sequencing data is a great challenge. In this work, a new computational pipeline, a Bayesian method for protein-DNA interaction with binding affinity ranking (BayesPI-BAR), is proposed for quantifying the effect of sequence variations on protein binding. BayesPI-BAR uses biophysical modeling of protein-DNA interactions to predict single nucleotide polymorphisms (SNPs) that cause significant changes in the binding affinity of a regulatory region for transcription factors (TFs). The method includes

SUBMITTER: Wang J 

PROVIDER: S-EPMC4666384 | biostudies-literature | 2015 Dec

REPOSITORIES: biostudies-literature