Bioinformatics/Biostatistics: Microarray Analysis

Part of the Methods in Molecular Biology book series (MIMB, volume 823)


The quantity and complexity of the molecular-level data generated in both research and clinical settings require the use of sophisticated, powerful computational interpretation techniques. It is for this reason that bioinformatic analysis of complex molecular profiling data has become a fundamental technology in the development of personalized medicine. This chapter provides a high-level overview of the field of bioinformatics and outlines several, classic bioinformatic approaches. The highlighted approaches can be aptly applied to nearly any sort of high-dimensional genomic, proteomic, or metabolomic experiments. Reviewed technologies in this chapter include traditional clustering analysis, the Gene Expression Dynamics Inspector (GEDI), GoMiner (GoMiner), Gene Set Enrichment Analysis (GSEA), and the Learner of Functional Enrichment (LeFE).

Key words

Bioinformatics Biostatistics Clustering Genomics Microarray 


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Copyright information

© Springer Science+Business Media, LLC 2012

Authors and Affiliations

  1. 1.InnoCentive Inc.WalthamUSA

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