Integrating heterogeneous microarray data sources using correlation signatures

Jaewoo Kang, Jiong Yang, Wanhong Xu, Pankaj Chopra

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

11 Citations (Scopus)

Abstract

Microarrays are one of the latest breakthroughs in experimental molecular biology. Thousands of different research groups generate tens of thousands of microarray gene expression profiles based on different tissues, species, and conditions. Combining such vast amount of microarray data sets is an important and yet challenging problem. In this paper, we introduce a "correlation signature" method that allows the coherent interpretation and integration of microarray data across disparate sources. The proposed algorithm first builds, for each gene (row) in a table, a correlation signature that captures the system-wide dependencies existing between the gene and the other genes within the table, and then compares the signatures across the tables for further analysis. We validate our framework with an experimental study using real microarray data sets, the result of which suggests that such an approach can be a viable solution for the microarray data integration and analysis problems.

Original languageEnglish
Title of host publicationLecture Notes in Bioinformatics (Subseries of Lecture Notes in Computer Science)
EditorsB. Ludascher, L. Raschid
Pages105-120
Number of pages16
Volume3615
Publication statusPublished - 2005
Externally publishedYes
EventSecond International Workshop on Data Integration in the Life Sciences, DILS 2005 - San Diego, CA, United States
Duration: 2005 Jul 202005 Jul 22

Other

OtherSecond International Workshop on Data Integration in the Life Sciences, DILS 2005
CountryUnited States
CitySan Diego, CA
Period05/7/2005/7/22

Fingerprint

Information Storage and Retrieval
Microarrays
Microarray Data
Signature
Gene
Microarray
Genes
Table
Transcriptome
Gene Expression Profile
Molecular Biology
Data Integration
Tables
Experimental Study
Data analysis
Molecular biology
Data integration
Research
Gene expression
Tissue

ASJC Scopus subject areas

  • Biochemistry, Genetics and Molecular Biology(all)
  • Biochemistry, Genetics and Molecular Biology (miscellaneous)
  • Computer Science(all)
  • Computer Science (miscellaneous)
  • Theoretical Computer Science

Cite this

Kang, J., Yang, J., Xu, W., & Chopra, P. (2005). Integrating heterogeneous microarray data sources using correlation signatures. In B. Ludascher, & L. Raschid (Eds.), Lecture Notes in Bioinformatics (Subseries of Lecture Notes in Computer Science) (Vol. 3615, pp. 105-120)

Integrating heterogeneous microarray data sources using correlation signatures. / Kang, Jaewoo; Yang, Jiong; Xu, Wanhong; Chopra, Pankaj.

Lecture Notes in Bioinformatics (Subseries of Lecture Notes in Computer Science). ed. / B. Ludascher; L. Raschid. Vol. 3615 2005. p. 105-120.

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

Kang, J, Yang, J, Xu, W & Chopra, P 2005, Integrating heterogeneous microarray data sources using correlation signatures. in B Ludascher & L Raschid (eds), Lecture Notes in Bioinformatics (Subseries of Lecture Notes in Computer Science). vol. 3615, pp. 105-120, Second International Workshop on Data Integration in the Life Sciences, DILS 2005, San Diego, CA, United States, 05/7/20.
Kang J, Yang J, Xu W, Chopra P. Integrating heterogeneous microarray data sources using correlation signatures. In Ludascher B, Raschid L, editors, Lecture Notes in Bioinformatics (Subseries of Lecture Notes in Computer Science). Vol. 3615. 2005. p. 105-120
Kang, Jaewoo ; Yang, Jiong ; Xu, Wanhong ; Chopra, Pankaj. / Integrating heterogeneous microarray data sources using correlation signatures. Lecture Notes in Bioinformatics (Subseries of Lecture Notes in Computer Science). editor / B. Ludascher ; L. Raschid. Vol. 3615 2005. pp. 105-120
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