Analysis of Microarray Gene Expression Data

Ting-Lee Mei-Ling

396 pages, parution le 01/03/2004

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Résumé

After genomic sequencing, microarray technology has emerged as a widely used platform for genomic studies in the life sciences. Microarray technology provides a systematic way to survey DNA and RNA variation. With the abundance of data produced from microarray studies, however, the ultimate impact of the studies on biology will depend heavily on data mining and statistical analysis. The contribution of this book is to provide readers with an integrated presentation of various topics on analyzing microarray data.

Written for: Biologists and statisticians interested in analyzing microarray data.

Sommaire

Part I: Genome Probing Using Microarrays
- Introduction
- DNA, RNA, Proteins, and Gene Expression
- Microarray Technology
- Inherent Variability in Array Data
- Background Noise
- Transformation and Normalization
- Missing Values in Array Data
- Saturated Intensity Readings
Part II: Statistical Models and Analysis
- Experimental Design
- ANOVA Models for Microarray Data
- Multiple Testing in Microarray Studies
- Permutation Tests in Microarray Data
- Bayesian Methods for Microarray Data
- Power and Sample Size Considerations
Part III: Unsupervised Exploratory Analysis
- Cluster Analysis
- Principal Components and Singular Value Decomposition
- Self-organizing Maps
Part IV: Supervised Learning Methods
- Discrimination and Classification
- Artificial Neural Networks
- Support Vector Machines

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Caractéristiques techniques

	PAPIER
Éditeur(s)	Kluwer Academic Publishers
Auteur(s)	Ting-Lee Mei-Ling
Parution	01/03/2004
Nb. de pages	396
Format	16 x 24
Couverture	Relié
Poids	780g
Intérieur	Noir et Blanc
EAN13	9780792370871
ISBN13	978-0-7923-7087-1