Analyzing array data using supervised methods

Research output: Contribution to journalArticle

Abstract

Pharmacogenomics is the application of genomic technologies to drug discovery and development, as well as for the elucidation of the mechanisms of drug action on cells and organisms. DNA microarrays measure genome-wide gene expression patterns and are an important tool for pharmacogenomic applications, such as the identification of molecular targets for drugs, toxicological studies and molecular diagnostics. Genome-wide investigations generate vast amounts of data and there is a need for computational methods to manage and analyze this information. Recently, several supervised methods, in which other information is utilized together with gene expression data, have been used to characterize genes and samples. The choice of analysis methods will influence the results and their interpretation, therefore it is important to be familiar with each method, its scope and limitations. Here, methods with special reference to applications for pharmacogenomics are reviewed.

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Research areas and keywords

Subject classification (UKÄ) – MANDATORY

  • Biophysics

Keywords

  • machine learning, genes, drug targets, DNA chip, diagnostic prediction, diagnostic classification, artificial neural networks, bioinformatics, microarray, support vector machines, target identification
Original languageEnglish
Pages (from-to)403-415
JournalPharmacogenomics
Volume3
Issue number3
Publication statusPublished - 2002
Publication categoryResearch
Peer-reviewedYes