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:
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GEOFFREY J. McLACHLAN, PhD, is Professor of Statistics at the University of Queensland, Australia, and the author of four very successful statistical texts.
KIM-ANH DO, PhD, is Professor of Biostatistics at the University of Texas MD Anderson Cancer Center in Houston, Texas.
CHRISTOPHE AMBROISE, PhD, is Lecturer at the Université de Technologie de Compiègne in France.
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:
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