Introduction to Statistical Methods to Analyze Large Data Sets: Principal Components Analysis

Sci. Signal., 13 September 2011
Vol. 4, Issue 190, p. tr3
DOI: 10.1126/scisignal.2001967

Introduction to Statistical Methods to Analyze Large Data Sets: Principal Components Analysis

  1. Neil R. Clark and
  2. Avi Ma’ayan*
  1. Department of Pharmacology and Systems Therapeutics and Systems Biology Center New York, Mount Sinai School of Medicine, New York, NY 10029, USA.
  1. *Corresponding author. E-mail, avi.maayan{at}mssm.edu

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.

Citation:

N. R. Clark and A. Ma’ayan, Introduction to Statistical Methods to Analyze Large Data Sets: Principal Components Analysis. Sci. Signal. 4, tr3 (2011).

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