Statistical approaches to use a model organism for regulatory sequences annotation of newly sequenced species.

ABSTRACT: A major goal of bioinformatics is the characterization of transcription factors and the transcriptional programs they regulate. Given the speed of genome sequencing, we would like to quickly annotate regulatory sequences in newly-sequenced genomes. In such cases, it would be helpful to predict sequence motifs by using experimental data from closely related model organism. Here we present a general algorithm that allow to identify transcription factor binding sites in one newly sequenced species by performing Bayesian regression on the annotated species. First we set the rationale of our method by applying it within the same species, then we extend it to use data available in closely related species. Finally, we generalise the method to handle the case when a certain number of experiments,

SUBMITTER: Lio P 

PROVIDER: S-EPMC3439465 | biostudies-literature | 2012

REPOSITORIES: biostudies-literature