Methods of Microarray Data Analysis II

Simon M. Lin, Kimberly F. Johnson1402071116, 9781402071119, 9780306475986

Microarray technology is a major experimental tool for functional genomic explorations, and will continue to be a major tool throughout this decade and beyond. The recent explosion of this technology threatens to overwhelm the scientific community with massive quantities of data. Because microarray data analysis is an emerging field, very few analytical models currently exist. Methods of Microarray Data Analysis II is the second book in this pioneering series dedicated to this exciting new field. In a single reference, readers can learn about the most up-to-date methods, ranging from data normalization, feature selection, and discriminative analysis to machine learning techniques.

Currently, there are no standard procedures for the design and analysis of microarray experiments. Methods of Microarray Data Analysis II focuses on a single data set, using a different method of analysis in each chapter. Real examples expose the strengths and weaknesses of each method for a given situation, aimed at helping readers choose appropriate protocols and utilize them for their own data set. In addition, web links are provided to the programs and tools discussed in several chapters. This book is an excellent reference not only for academic and industrial researchers, but also for core bioinformatics/genomics courses in undergraduate and graduate programs.

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Table of contents :
Preliminaries……Page 1
Contents……Page 6
Contributors……Page 8
Acknowledgements……Page 10
Preface……Page 12
Introduction……Page 14
AN INTRODUCTION TO DNA MICROARRAYS……Page 22
EXPERIMENTAL DESIGN FOR GENE MICROARRAY EXPERIMENTS AND DIFFERENTIAL EXPRESSION ANALYSIS……Page 36
MICROARRAY DATA PROCESSING AND ANALYSIS……Page 56
BIOLOGY-DRIVEN CLUSTERING OF MICROARRAY DATA……Page 78
XTRACTING GLOBAL STRUCTURE FROM GENE EXPRESSION PROFILES……Page 94
SUPERVISED NEURAL NETWORKS FOR CLUSTERING……Page 104
BAYESIAN DECOMPOSITION ANALYSIS OF GENE EXPRESSION IN YEAST DELETION MUTANTS……Page 118
USING FUNCTIONAL GENOMIC UNITS TO CORROBORATE……Page 136
FISHING EXPEDITION……Page 152
MODELING PHARMACOGENOMICS OF THE NCI-60 ANTICANCER DATA SET……Page 164
ANALYSIS OF GENE EXPRESSION PROFILES AND DRUG ACTIVITY PATTERNS BY CLUSTERING AND BAYESIAN NETWORK LEARNING……Page 182
EVALUATION OF CURRENT METHODS OF TESTING DIFFERENTIAL GENE EXPRESSION AND BEYOND……Page 198
EXTRACTING KNOWLEDGE FROM GENOMIC EXPERIMENTS BY INCORPORATING THE BIOMEDICAL LITERATURE……Page 208
Index……Page 226