Statistical modeling of transcription factor binding affinities predicts regulatory interactions.

ABSTRACT: Recent experimental and theoretical efforts have highlighted the fact that binding of transcription factors to DNA can be more accurately described by continuous measures of their binding affinities, rather than a discrete description in terms of binding sites. While the binding affinities can be predicted from a physical model, it is often desirable to know the distribution of binding affinities for specific sequence backgrounds. In this paper, we present a statistical approach to derive the exact distribution for sequence models with fixed GC content. We demonstrate that the affinity distribution of almost all known transcription factors can be effectively parametrized by a class of generalized extreme value distributions. Moreover, this parameterization also describes the affinity distr

SUBMITTER: Manke T 

PROVIDER: S-EPMC2266803 | biostudies-literature | 2008 Mar

REPOSITORIES: biostudies-literature