Methods of Microarray Data Analysis II

Chapter 1 Introduction

Chapter 2 An Introduction to DNA Microarrays

Chapter 3 Experimental Design for Gene Microarray Experiments and Differential Expression Analysis

Chapter 4 Microarray Data Processing and Analysis

Chapter 5 Biology-driven Clustering of Microarray Data

Chapter 6 Extracting Global Structure from Gene Expression Profiles

Chapter 7 Supervised Neural Networks for Clustering Conditions in DNA Array Data After Reducing Noise by Clustering Gene Expression Profiles

Chapter 8 Bayesian Decomposition Analysis of Gene Expression in Yeast Deletion Mutants

Chapter 9 Using Functional Genomic Units to Corroborate User Experiments with the Rosetta Compendium

Chapter 10 Fishing Expedition - a Supervised Approach to Extract Patterns from a Compendium of Expression Profiles

Chapter 11 Modeling Pharmacogenomics of the NCI-60 Anticancer Data Set: Utilizing Kernel Pls to Correlate the Microarray Data to Therapeutic Responses

Chapter 12 Analysis of Gene Expression Profiles and Drug Activity Patterns by Clustering and Bayesian Network Learning

Chapter 13 Evaluation of Current Methods of Testing Differential Gene expression and Beyond

Chapter 14 Extracting Knowledge from Genomic Experiments by Incorporating the Biomedical Literature