Efficiently finding regulatory elements using correlation with gene expression

Hideo Bannai, Shunsuke Inenaga, Ayumi Shinohara, Masayuki Takeda, Satoru Miyano

Research output: Contribution to journalArticle

19 Citations (Scopus)

Abstract

We present an efficient algorithm for detecting putative regulatory elements in the upstream DNA sequences of genes, using gene expression information obtained from microarray experiments. Based on a generalized suffix tree, our algorithm looks for motif patterns whose appearance in the upstream region is most correlated with the expression levels of the genes. We are able to find the optimal pattern, in time linear in the total length of the upstream sequences. We implement and apply our algorithm to publicly available microarray gene expression data, and show that our method is able to discover biologically significant motifs, including various motifs which have been reported previously using the same data set. We further discuss applications for which the efficiency of the method is essential, as well as possible extensions to our algorithm.

Original languageEnglish
Pages (from-to)273-288
Number of pages16
JournalJournal of Bioinformatics and Computational Biology
Volume2
Issue number2
DOIs
Publication statusPublished - 2004 Jun 1
Externally publishedYes

Keywords

  • Gene expression and regulatory elements
  • Pattern discovery
  • Suffix
  • Tree

ASJC Scopus subject areas

  • Biochemistry
  • Molecular Biology
  • Computer Science Applications

Fingerprint Dive into the research topics of 'Efficiently finding regulatory elements using correlation with gene expression'. Together they form a unique fingerprint.

  • Cite this