Exploring Microarray Data with Correspondence Analysis
作者： Stanislav Busygin , Panos M. Pardalos
DOI: 10.1007/978-0-387-69319-4_2
关键词: Computational biology 、 DNA microarray 、 Microarray databases 、 Microarray 、 Correspondence analysis 、 Singular value decomposition 、 Microarray analysis techniques 、 Computer science 、 High dimensionality
摘要: Due to the rapid development of DNA microarray chips it has become possible discover and predict genetic patterns relevant for various diseases on basis exploration massive data sets provided by probes. A number mining techniques have been used such achieve desirable results. However, high dimensionality uncertain accuracy datasets remain major obstacles in revealing most crucial factors determining a particular disease. This chapter describes processing technique based correspondence analysis that helps handle this issue.
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