Automated analysis of multivariate nonlinear gene relations based on cDNA microarray expression data

Seungchan Kim, Edward R. Dougherty, Michael L. Bittner, Yidong Chen, Krishnamoorthy Sivakumar, Paul Meltzer, Jeffery M. Trent

Research output: Contribution to journalConference articlepeer-review


A cDNA microarray is a complex biochemical-optical system whose purpose is the simultaneous measurement of gene expression for thousands of genes. This paper describes a general statistical environment for finding associations among gene expression patterns, and between genes and external conditions, via the coefficient of determination. This coefficient measures the degree to which the transcriptional levels of an observed gene set can be used to improve the prediction of the transcriptional state of a target gene relative to the best possible prediction in the absence of observations. Various aspects of the method are discussed: prediction quantification, design of predictors given small numbers of replicated microarrays, and constrained prediction using ternary perceptrons. A main focus is the supporting software and its facilities for data analysis and visualization.

Original languageEnglish (US)
Pages (from-to)150-155
Number of pages6
JournalProceedings of SPIE - The International Society for Optical Engineering
StatePublished - 2000
Externally publishedYes
EventAdvances in Nucleic Acid and Protein Analyses, Manipulation, and Sequencing - San Jose, CA, USA
Duration: Jan 26 2000Jan 27 2000

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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