Exploration and Analysis of DNA Microarray and Protein Array Data

by Amaratunga, Dhammika; Cabrera, Javier

• ISBN13: 9780471273981
• ISBN10: 0471273988
• Format: Hardcover
• Copyright: 2003-10-21
• Publisher: Wiley-Interscience

Summary

The emergence of genomics, the study of genes, is one of the major scientific revolutions of this century. Microarrays, a method used to analyze numerous DNA samples rapidly, enables scientists to make sense of this mountain of data using statistical analysis. They are being used in such areas of biomedical research as studying patterns for gene activity that cause cancers to spread. This book presents a comprehensive methodology for analyzing DNA microarray and protein array data. The most comprehensive treatment of this important emerging field, Exploration and Analysis of DNA Microarray and Protein Array Data includes: A review of basic molecular biology and a chapter introducing microarrays and their preparation Chapters on processing scanned images, preprocessing microarray data, group comparative experiments, and other designs Discussions of clustering, protein arrays, and applications for diagnostic tools Ample exercises assist absorbtion

Author Biography

<b>DHAMMIKA AMARATUNGA, PhD</b>, is a Senior Research Fellow in the Nonclinical Biostatistics Department at Johnson &amp; Johnson Pharmaceutical Research &amp; Development, LLC. He has a doctorate in statistics from Princeton University and has been working in the pharmaceutical industry for over fifteen years. His research interests include analysis of large multivariate data sets, particularly those generated by functional genomics research, robust and resistant statistical methods, linear and nonlinear modeling, and biostatistics. <p> <b>JAVIER CABRERA, PhD</b>, is an Associate Professor in the Department of Statistics at Rutgers University. He has a doctorate in statistics from Princeton University and has over fifty publications in applied statistics. His research interests include DNA microarray, data mining of biopharmaceutical databases, computer vision, statistical computing and graphics, robustness, and biostatistics.

Table of Contents

Preface.

A Brief Introduction.

Genomics Basics.

Microarrays.

Processing the Scanned Image.

Preprocessing Microarray Data.

Summarization.

Two-Group Comparative Experiments.

Model-Based Inference and Experimental Design Considerations.

Pattern Discovery.

Class Prediction.

Protein Arrays.

References.