Analysis Overview

  • V. J. Carey
  • R. Gentleman
Part of the Statistics for Biology and Health book series (SBH)


Chapters in this part of the book address tasks common in the downstream analysis (after preprocessing) of high-dimensional data. The basic assumption is that preprocessing has led to a sample for which it is reasonable to make comparisons between samples or between feature-vectors assembled across samples. Most examples are based on microarray data, but the principles are much broader and apply to many other sources of data. In this overview, the basic concepts and assumptions are briefly sketched.


Microarray Data Expression Measure Array Comparative Genomic Hybridization cDNA Array Computational Learning Theory 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

Copyright information

© Springer Science+Business Media, Inc. 2005

Authors and Affiliations

  • V. J. Carey
  • R. Gentleman

There are no affiliations available

Personalised recommendations