Geoffrey McLachlan & Kim-Anh Do 
Analyzing Microarray Gene Expression Data [PDF ebook] 

A multi-discipline, hands-on guide to microarray analysis of
biological processes

Analyzing Microarray Gene Expression Data provides a
comprehensive review of available methodologies for the analysis of
data derived from the latest DNA microarray technologies. Designed
for biostatisticians entering the field of microarray analysis as
well as biologists seeking to more effectively analyze their own
experimental data, the text features a unique interdisciplinary
approach and a combined academic and practical perspective that
offers readers the most complete and applied coverage of the
subject matter to date.

Following a basic overview of the biological and technical
principles behind microarray experimentation, the text provides a
look at some of the most effective tools and procedures for
achieving optimum reliability and reproducibility of research
results, including:

* An in-depth account of the detection of genes that are
differentially expressed across a number of classes of tissues

* Extensive coverage of both cluster analysis and discriminant
analysis of microarray data and the growing applications of both
methodologies

* A model-based approach to cluster analysis, with emphasis on
the use of the EMMIX-GENE procedure for the clustering of tissue
samples

* The latest data cleaning and normalization procedures

* The uses of microarray expression data for providing important
prognostic information on the outcome of disease

Зміст

Preface.

1. Microarrays in Gene Expression Studies.

2. Cleaning and Normalization.

3. Some Cluster Analysis Methods.

4. Clustering of Tissue Samples.

5. Screening and Clustering of Genes.

6. Discriminant Analysis.

7. Supervised Classification of Tissue Samples.

8. Linking Microarray Data with Survival Analysis.

References.

Author Index.

Subject Index.

Про автора

GEOFFREY J. Mc LACHLAN, Ph D, is Professor of Statistics at the
University of Queensland, Australia, and the author of four very
successful statistical texts.

KIM-ANH DO, Ph D, is Professor of Biostatistics at the University
of Texas MD Anderson Cancer Center in Houston, Texas.

CHRISTOPHE AMBROISE, Ph D, is Lecturer at the Université de
Technologie de Compiègne in France.