An Approach To Canonical Analysis Of Singular Data

An Approach to Canonical Analysis of Singular Data

A Practical Approach to Microarray Data Analysis

In the past several years, DNA microarray technology has attracted tremendous interest in both the scientific community and in industry. With its ability to simultaneously measure the activity and interactions of thousands of genes, this modern technology promises unprecedented new insights into mechanisms of living systems. Currently, the primary applications of microarrays include gene discovery, disease diagnosis and prognosis, drug discovery (pharmacogenomics), and toxicological research (toxicogenomics). Typical scientific tasks addressed by microarray experiments include the identification of coexpressed genes, discovery of sample or gene groups with similar expression patterns, identification of genes whose expression patterns are highly differentiating with respect to a set of discerned biological entities (e.g., tumor types), and the study of gene activity patterns under various stress conditions (e.g., chemical treatment). More recently, the discovery, modeling, and simulation of regulatory gene networks, and the mapping of expression data to metabolic pathways and chromosome locations have been added to the list of scientific tasks that are being tackled by microarray technology. Each scientific task corresponds to one or more so-called data analysis tasks. Different types of scientific questions require different sets of data analytical techniques. Broadly speaking, there are two classes of elementary data analysis tasks, predictive modeling and pattern-detection. Predictive modeling tasks are concerned with learning a classification or estimation function, whereas pattern-detection methods screen the available data for interesting, previously unknown regularities or relationships.

Recent Advances in Statistical Research and Data Analysis

Recent Advances in Statistical Research and Data Analysis is a collection of papers presented at the symposium of the same name, held in Tokyo by the Center for Information on Statistical Science of the Institute of Statistical Mathematics (ISM). Under the auspices of the Ministry of Education, Culture, Sports, Science and Technology of Japan, the ISM has created visiting professorships and organized symposia to promote collaboration between researchers from Japan and those from other countries. At the symposium on recent advances in statistical research and data analysis, the keynote speaker was Visiting Professor Anthony J. Hayter. This book includes Prof. Hayter's address as well as papers from special lectures that were presented at the symposium. All the contributions are concerned with theory and methodology for real data and thus will benefit researchers, students, and others engaged in data analysis.