Clustering analysis for gene expression data

Yidong Chen, Olga Ermolaeva, Michael Bittner, Paul Meltzer, Jeffrey Trent, Edward R. Dougherty, Sinan Batman

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

Abstract

The recent development of cDNA microarray allows ready access to large amount gene expression patterns for many genetic materials. Gene expression of tissue samples can be quantitatively analyzed by hybridizing fluor-tagged mRNA to targets on a cDNA microarray. Ratios of average expression level arising from cohybridized normal and pathological samples are extracted via image segmentation, thus the gene expression pattern are obtained. The gene expression in a given biological process may provide a fingerprint of the sample development, or response to certain treatment. We propose a K-mean based algorithm in which gene expression levels fluctuate in parallel will be clustered together. The resulting cluster suggests some functional relationships between genes, and some known genes belongs to a unique functional classes shall provide indication for unknown genes in the same clusters.

Original languageEnglish (US)
Title of host publicationProceedings of SPIE - The International Society for Optical Engineering
PublisherSociety of Photo-Optical Instrumentation Engineers
Pages422-428
Number of pages7
ISBN (Print)0819430722
StatePublished - Jan 1 1999
EventProceedings of the 1999 Advances in Fluorescence Sensing Technology - San Jose, CA, USA
Duration: Jan 24 1999Jan 27 1999

Publication series

NameProceedings of SPIE - The International Society for Optical Engineering
Volume3602
ISSN (Print)0277-786X

Other

OtherProceedings of the 1999 Advances in Fluorescence Sensing Technology
CitySan Jose, CA, USA
Period1/24/991/27/99

ASJC Scopus subject areas

  • Electronic, Optical and Magnetic Materials
  • Condensed Matter Physics
  • Computer Science Applications
  • Applied Mathematics
  • Electrical and Electronic Engineering

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  • Cite this

    Chen, Y., Ermolaeva, O., Bittner, M., Meltzer, P., Trent, J., Dougherty, E. R., & Batman, S. (1999). Clustering analysis for gene expression data. In Proceedings of SPIE - The International Society for Optical Engineering (pp. 422-428). (Proceedings of SPIE - The International Society for Optical Engineering; Vol. 3602). Society of Photo-Optical Instrumentation Engineers.