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Pharmaceutical target identification by gene expression analysis.

M G Walker1

  • 1Incyte Genomics, 3174 Proter Dr, Palo Alto, California, USA. mwalker@incyte.com

Mini Reviews in Medicinal Chemistry
|October 9, 2002
PubMed
Summary
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Identifying novel drug targets is challenging. Gene expression analysis offers a way to find potential pharmaceutical targets by examining gene function and co-expression patterns, aiding in drug discovery.

Area of Science:

  • Genomics
  • Bioinformatics
  • Pharmacology

Background:

  • Many newly discovered human genes lack known functions and are difficult to identify as drug targets.
  • Gene expression analysis provides a valuable alternative approach to infer gene functions and identify potential therapeutic targets.

Purpose of the Study:

  • To review statistical methods for gene expression analysis to identify potential pharmaceutical targets.
  • To illustrate differential gene expression and co-expression analyses for functional genomics.

Main Methods:

  • Differential gene expression analysis: discriminant analysis, t-tests, analysis of variance.
  • Co-expression analysis: correlation, clustering, chi-square methods.
  • Application of expression analysis to identify cardiomyopathy-associated genes.

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Main Results:

  • Statistical methods can effectively analyze gene expression data to infer gene function.
  • Co-expression analysis can reveal relationships between genes, highlighting potential disease associations.
  • Expression analysis successfully identified co-expressed genes linked to cardiomyopathy.

Conclusions:

  • Gene expression analysis is a powerful tool for discovering novel drug targets among uncharacterized genes.
  • Methods like differential and co-expression analysis are crucial for functional genomics and pharmaceutical research.
  • This approach aids in identifying genes associated with complex diseases such as cardiomyopathy.