An algorithm for identifying novel targets of transcription factor families: application to hypoxia-inducible factor 1 targets.

ABSTRACT: Efficient and effective analysis of the growing genomic databases requires the development of adequate computational tools. We introduce a fast method based on the suffix tree data structure for predicting novel targets of hypoxia-inducible factor 1 (HIF-1) from huge genome databases. The suffix tree data structure has two powerful applications here: one is to extract unknown patterns from multiple strings/sequences in linear time; the other is to search multiple strings/sequences using multiple patterns in linear time. Using 15 known HIF-1 target gene sequences as a training set, we extracted 105 common patterns that all occur in the 15 training genes using suffix trees. Using these 105 common patterns along with known subsequences surrounding HIF-1 binding sites from the literature, the

SUBMITTER: Jiang Y 

PROVIDER: S-EPMC2664698 | biostudies-literature | 2009

REPOSITORIES: biostudies-literature