Front Matter; Introduction to Genomic and Proteomic Data Analysis; Design Principles for Microarray Investigations; Pre-Processing DNA Microarray Data; Pre-Processing Mass Spectrometry Data; Visualization in Genomics and Proteomics; Clustering -- Class Discovery in the Post-Genomic Era; Feature Selection and Dimensionality Reduction in Genomics and Proteomics; Resampling Strategies for Model Assessment and Selection; Classification of Genomic and Proteomic Data Using Support Vector Machines; Networks in Cell Biology; Identifying Important Explanatory Variables for Time-Varying Outcomes
Summary
To exploit data obtained from experimental and observational studies, life scientists need to understand the analytical techniques and methods from statistics and data mining. These techniques are not easily accessible to life scientists working on genomics and proteomics problems. This book aims to present these analytical methods
