A data mining method to predict transcriptional regulatory sites based on differentially expressed genes in human genome

Hsien Da Huang, Huei Lin Chang, Tsung Shan Tsou, Baw Jhiune Liu, Cheng Yan Kao, Jorng Tzong Horng

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

4 Scopus citations

Abstract

Very large-scale gene expression analysis, i.e., UniGene and dbEST, are provided to find those genes with significantly differential expression in specific tissues. The differentially expressed genes in a specific tissue are potentially regulated concurrently by a combination of transcription factors. This study attempts to mine putative binding sites on how combinations of the known regulatory sites homologs and over-represented repetitive elements are distributed in the promoter regions of considered groups of differentially expressed genes. We propose a data mining approach to statistically discover the significantly tissue-specific combinations of known site homologs and over-represented repetitive sequences, which are distributed in the promoter regions of differentially gene groups. The association rules mined would facilitate to predict putative regulatory elements and identify genes potentially co-regulated by the putative regulatory elements.

Original languageEnglish
Title of host publicationProceedings - 3rd IEEE Symposium on BioInformatics and BioEngineering, BIBE 2003
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages297-304
Number of pages8
ISBN (Electronic)0769519075, 9780769519074
DOIs
StatePublished - 2003
Event3rd IEEE Symposium on BioInformatics and BioEngineering, BIBE 2003 - Bethesda, United States
Duration: 10 Mar 200312 Mar 2003

Publication series

NameProceedings - 3rd IEEE Symposium on BioInformatics and BioEngineering, BIBE 2003

Conference

Conference3rd IEEE Symposium on BioInformatics and BioEngineering, BIBE 2003
Country/TerritoryUnited States
CityBethesda
Period10/03/0312/03/03

Keywords

  • Data mining
  • Gene expression
  • Regulatory site
  • Transcription factor

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