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Sci. Signal., 13 September 2011 TEACHING RESOURCESIntroduction to Statistical Methods to Analyze Large Data Sets: Principal Components AnalysisNeil R. Clark and Avi Maayan* Department of Pharmacology and Systems Therapeutics and Systems Biology Center New York, Mount Sinai School of Medicine, New York, NY 10029, USA. Abstract: This Teaching Resource provides lecture notes, slides, and a problem set for a series of lectures from a course entitled "Systems Biology: Biomedical Modeling." The materials are a lecture introducing the mathematical concepts behind principal components analysis (PCA). The lecture describes how to handle large data sets with correlation methods and unsupervised clustering with this popular method of analysis, PCA. * Corresponding author. E-mail, avi.maayan{at}mssm.edu
Citation: N. R. Clark, A. Maayan, Introduction to Statistical Methods to Analyze Large Data Sets: Principal Components Analysis. Sci. Signal. 4, tr3 (2011). The editors suggest the following Related Resources on Science sites:In Science Signaling
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Science Signaling. ISSN 1937-9145 (online), 1945-0877 (print). Pre-2008: Science's STKE. ISSN 1525-8882