Abstract
In a companion chapter in this volume, Wilson et al. (this volume, chapter by Wilson et al.) provide a detailed account of the experimental design and statistical analysis of microarray data. Their chapter is of interest to researchers planning microarray experiments capable of yielding data that can be statistically analyzed to insure reliable levels of confidence. In contrast, the present chapter emphasizes what can be done with the gathered data so as to simplify the huge task of interpreting the expression levels of tens of thousands of genes. In the companion chapter the authors assume the availability of statistical programs that are often used in the design of experiments. In this chapter we explore in greater detail the algorithms that process the collected data to obtain further information about cell behavior. Many of the algorithms described here aim at grouping similar data. We also explore microarray usage that is not addressed in the companion chapter.