Analysis of Microarray Gene Expression Data

Published by Springer (formerly Kluwer Academic Publishers), 2004

On-line order from Springer

Table of Contents

Part I: Genome Probing Using Microarrays.

1. Introduction.
2. DNA, RNA, Proteins, and Gene Expression.
3. Microarray Technology.
4. Inherent Variability in Array Data.
5. Background Noise.
6. Transformation and Normalization.
7. Missing Values in Array Data.
8. Saturated Intensity Readings.

Part II: Statistical Models and Analysis.

9. Experimental Design.
10. ANOVA Models for Microarray Data.
11. Multiple Testing in Microarray Studies.
12. Permutation Tests in Microarray Data.
13. Bayesian Methods for Microarray Data.
14. Power and Sample Size Considerations.

Part III: Unsupervised Exploratory Analysis.

15. Cluster Analysis.
16. Principal Components and Singular Value Decomposition.
17. Self-organizing Maps.

Part IV: Supervised Learning Methods.

18. Discrimination and Classification.
19. Artificial Neural Networks.
20. Support Vector Machines.