Bayesian Modeling in Bioinformatics discusses the development and application of Bayesian statistical methods for the analysis of high-throughput bioinformatics data arising from problems in molecular and structural biology and disease-related medical research, such as cancer. It presents a broad overview of statistical inference, clustering, and classification problems in two main high-throughput platforms: microarray gene expression and phylogenic analysis.

The book explores Bayesian techniques and models for detecting differentially expressed genes,...

Extreme events are critical in risk analysis in the fields such as finance, insurance, climate change and hydrology. Examples are maxima of temperature, wind speed, insurance claims, financial loss, and flood level. Extreme value theory plays a central role in risk management, extreme value modeling, and strategic adaptation. This book covers the latest applications of extreme value modeling and risk analysis. The book uses advanced statistical methodologies to demonstrate difference between extreme observations and the mean state data.