Methods of Microarray Data Analysis II

Contributors. Acknowledgements. Preface. Introduction. An Introduction to DNA Microarrays; P. McConnell, et al. Experimental Design for Gene Microarray Experiments and Differential Expression Analysis; G.V. Bobashev, et al. Microarray Data Processing and Analysis; J. Dopazo. Biology-Driven Clustering of Microarray Data; K.R. Coombes, et al. Extracting Global Structure from Gene Expression Profiles; C. Fowlkes, et al. Supervised Neural Networks for Clustering Conditions in DNA Array Data after Reducing Noise by Clustering Gene Expression Profiles; A. Mateos, et al. Bayesian Decomposition Analysis of Gene Expression in Yeast Deletion Mutants; G. Bidaut, et al. Using Functional Genomic Units to Corroborate User Experiments with the Rosetta Compendium; S.M. Lin, et al. Fishing Expedition - A Supervised Approach to Extract Patterns from a Compendium of Expression Profiles; Z. Zhang, et al. Modeling Pharmacogenomics of the NCI-60 Anticancer Data Set: Utilizing Kernel PLS to Correlate the Microarray Data to Therapeutic Responses; N. Dasgupta, et al. Analysis of Gene Expression Profiles and Drug Activity Patterns by Clustering and Bayesian Network Learning; Jeong-Ho Chang, et al. Evaluation of Current Methods of Testing Differential Gene Expression and Beyond; Y.-J. Li, et al. Extracting Knowledge from Genomic Experiments by Incorporating the Biomedical Literature; J.P. Sluka. Index.

Simon M. Lin is Manager of Duke Bioinformatics Shared Resource, Duke University Medical Center. Kimberly F. Johnson is Director of Duke Cancer Center Information Systems and Director of Duke Bioinformatics Shared Resource, Duke University Medical Center.