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Microarray bioinformatics.

Authors
Type
Published Article
Journal
Methods in Molecular Biology
1064-3745
Publication Date
Volume
671
Pages
295–320
Identifiers
DOI: 10.1007/978-1-59745-551-0_18
PMID: 20967638
Source
Medline
License
Unknown

Abstract

Bioinformatics has become an increasingly important tool for molecular biologists, especially for the analysis of microarray data. Microarrays can produce vast amounts of information requiring a series of consecutive analyses to render the data interpretable. The direct output of microarrays cannot be directly interpreted to show differences in settings, conditions of samples, or time points. To make microarray experiments interpretable, it is necessary that a series of algorithms and approaches be applied. After normalization of generated data, which is necessary to make a comparison feasible, significance analysis, clustering of samples and biological compounds of interest and visualization are generally performed. This chapter will focus on providing a basic understanding of the generally approaches and algorithms currently employed in microarray bioinformatics.

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