Using sequence-specific chemical and structural properties of DNA to predict transcription factor binding sites.

ABSTRACT: An important step in understanding gene regulation is to identify the DNA binding sites recognized by each transcription factor (TF). Conventional approaches to prediction of TF binding sites involve the definition of consensus sequences or position-specific weight matrices and rely on statistical analysis of DNA sequences of known binding sites. Here, we present a method called SiteSleuth in which DNA structure prediction, computational chemistry, and machine learning are applied to develop models for TF binding sites. In this approach, binary classifiers are trained to discriminate between true and false binding sites based on the sequence-specific chemical and structural features of DNA. These features are determined via molecular dynamics calculations in which we consider each base in

SUBMITTER: Bauer AL 

PROVIDER: S-EPMC2987836 | biostudies-literature | 2010 Nov

REPOSITORIES: biostudies-literature