Identifying biologically relevant genes via multiple heterogeneous data sources

Zheng Zhao, Jiangxin Wang, Huan Liu, Jieping Ye, Yung Chang

Research output: Chapter in Book/Report/Conference proceedingConference contribution

11 Scopus citations

Abstract

Selection of genes that are differentially expressed and critical to a particular biological process has been a major challenge in post-array analysis. Recent development in bioinformatics has made various data sources available such as mRNA and miRNA expression profiles, biological pathway and gene annotation, etc. Efficient and effective integration of multiple data sources helps enrich our knowledge about the involved samples and genes for selecting genes bearing significant biological relevance. In this work, we studied a novel problem of multi-source gene selection: given multiple heterogeneous data sources (or data sets), select genes from expression profiles by integrating information from various data sources. We investigated how to effectively employ information contained in multiple data sources to extract an intrinsic global geometric pattern and use it in covariance analysis for gene selection. We designed and conducted experiments to systematically compare the proposed approach with representative methods in terms of statistical and biological significance, and showed the efficacy and potential of the proposed approach with promising findings.

Original languageEnglish (US)
Title of host publicationKDD 2008 - Proceedings of the 14th ACMKDD International Conference on Knowledge Discovery and Data Mining
Pages839-847
Number of pages9
DOIs
StatePublished - 2008
Event14th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, KDD 2008 - Las Vegas, NV, United States
Duration: Aug 24 2008Aug 27 2008

Publication series

NameProceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining

Other

Other14th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, KDD 2008
CountryUnited States
CityLas Vegas, NV
Period8/24/088/27/08

Keywords

  • Bioinformatics
  • Gene selection
  • Information integration

ASJC Scopus subject areas

  • Software
  • Information Systems

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