High resolution models of transcription factor-DNA affinities improve in vitro and in vivo binding predictions.

ABSTRACT: Accurately modeling the DNA sequence preferences of transcription factors (TFs), and using these models to predict in vivo genomic binding sites for TFs, are key pieces in deciphering the regulatory code. These efforts have been frustrated by the limited availability and accuracy of TF binding site motifs, usually represented as position-specific scoring matrices (PSSMs), which may match large numbers of sites and produce an unreliable list of target genes. Recently, protein binding microarray (PBM) experiments have emerged as a new source of high resolution data on in vitro TF binding specificities. PBM data has been analyzed either by estimating PSSMs or via rank statistics on probe intensities, so that individual sequence patterns are assigned enrichment scores (E-scores). This represen

SUBMITTER: Agius P 

PROVIDER: S-EPMC2936517 | biostudies-literature | 2010 Sep

REPOSITORIES: biostudies-literature