Exploration and Analysis of DNA Microarray and Other High Dimensional Data

Praise for the First Edition

“…extremely well written…a comprehensive and up-to-date overview of this important field.” – Journal of Environmental Quality

Exploration and Analysis of DNA Microarray and Other High-Dimensional Data, Second Edition provides comprehensive coverage of recent advancements in microarray data analysis. A cutting-edge guide, the Second Edition demonstrates various methodologies for analyzing data in biomedical research and offers an overview of the modern techniques used in microarray technology to study patterns of gene activity.

The new edition answers the need for an efficient outline of all phases of this revolutionary analytical technique, from preprocessing to the analysis stage. Utilizing research and experience from highly-qualified authors in fields of data analysis, Exploration and Analysis of DNA Microarray and Other High-Dimensional Data, Second Edition features:

• A new chapter on the interpretation of findings that includes a discussion of signatures and material on gene set analysis, including network analysis
• New topics of coverage including ABC clustering, biclustering, partial least squares, penalized methods, ensemble methods, and enriched ensemble methods
• Updated exercises to deepen knowledge of the presented material and provide readers with resources for further study

The book is an ideal reference for scientists in biomedical and genomics research fields who analyze DNA microarrays and protein array data, as well as statisticians and bioinformatics practitioners. Exploration and Analysis of DNA Microarray and Other High-Dimensional Data, Second Edition is also a useful text for graduate-level courses on statistics, computational biology, and bioinformatics.

DHAMMIKA AMARATUNGA, PhD, is Senior Director and Janssen Fellow in the Nonclinical Statistics and Computing Department at Janssen R&D, a Johnson & Johnson pharmaceutical company. His research interests include analysis of large multivariate data sets generated by functional genomics research, robust and resistant statistical methods, linear and nonlinear modeling, and biostatistics.

JAVIER CABRERA, PhD, is Full Professor in the Department of Statistics at Rutgers University. He has published over 100 articles in his areas of research interest, which include DNA microarray, data mining of biopharmaceutical databases, computer vision, statistical computing and graphics, robustness, and biostatistics. He has also lectured at Cold Spring Harbor Laboratory, The Hong Kong University of Science and Technology, and National University of Singapore.

ZIV SHKEDY, PhD, is Associate Professor and Statistical Consultant in the Interuniversity Institute for Biostatistics and Statistical Bioinformatics, Center for Statistics at Hasselt University, Belgium. He has published numerous journal articles on the topics of clinical and non-clinical trials, modeling infectious disease data, dose-response analysis, Bayesian modeling, bioinformatics, and analysis of gene expression data.