A cutting-edge guide to the analysis of DNA microarray dataGenomics is one of the major scientific revolutions of this century, and the use of microarrays to rapidly analyze numerous DNA samples has enabled scientists to make sense of mountains of genomic data through statistical analysis. Today, mi
Analyzing Microarray Gene Expression Data (Wiley Series in Probability and Statistics)
β Scribed by Geoffrey J. McLachlan, Kim-Anh Do, Christophe Ambroise
- Publisher
- Wiley-Interscience
- Year
- 2004
- Tongue
- English
- Leaves
- 349
- Series
- Wiley Series in Probability and Statistics
- Edition
- 1
- Category
- Library
No coin nor oath required. For personal study only.
β¦ Synopsis
A multi-discipline, hands-on guide to microarray analysis of biological processesAnalyzing 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 tissuesExtensive coverage of both cluster analysis and discriminant analysis of microarray data and the growing applications of both methodologiesA model-based approach to cluster analysis, with emphasis on the use of the EMMIX-GENE procedure for the clustering of tissue samplesThe latest data cleaning and normalization proceduresThe uses of microarray expression data for providing important prognostic information on the outcome of disease
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