Transcription factor binding element detection using functional clustering of mutant expression data.

ABSTRACT: As a powerful tool to reveal gene functions, gene mutation has been used extensively in molecular biology studies. With high throughput technologies, such as DNA microarray, genome-wide gene expression changes can be monitored in mutants. Here we present a simple approach to detect the transcription-factor-binding motif using microarray expression data from a mutant in which the relevant transcription factor is deleted. A core part of our approach is clustering of differentially expressed genes based on functional annotations, such as Gene Ontology (GO). We tested our method with eight microarray data sets from the Rosetta Compendium and were able to detect canonical binding motifs for at least four transcription factors. With the support of chromatin IP chip data, we also predict a possib

SUBMITTER: Chen G 

PROVIDER: S-EPMC419446 | biostudies-literature | 2004

REPOSITORIES: biostudies-literature