Predicting eukaryotic transcriptional cooperativity by Bayesian network integration of genome-wide data.

ABSTRACT: Transcriptional cooperativity among several transcription factors (TFs) is believed to be the main mechanism of complexity and precision in transcriptional regulatory programs. Here, we present a Bayesian network framework to reconstruct a high-confidence whole-genome map of transcriptional cooperativity in Saccharomyces cerevisiae by integrating a comprehensive list of 15 genomic features. We design a Bayesian network structure to capture the dominant correlations among features and TF cooperativity, and introduce a supervised learning framework with a well-constructed gold-standard dataset. This framework allows us to assess the predictive power of each genomic feature, validate the superior performance of our Bayesian network compared to alternative methods, and integrate genomic featur

SUBMITTER: Wang Y 

PROVIDER: S-EPMC2764433 | biostudies-literature | 2009 Oct

REPOSITORIES: biostudies-literature