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This book is an edited volume, the goal of which is to provide an overview of the current
state-of-the-art in statistical methods applied to problems in structural bioinformatics (and in …

Background Many mathematical models have now been employed across every area of
systems biology. These models increasingly involve large numbers of unknown parameters …

Bayesian modeling has become an indispensable tool for ecological research because it is
uniquely suited to deal with complexity in a statistically coherent way. This textbook provides …

Motivation: Gene identification and gene discovery in new genomic sequences is one of the
most timely computational questions addressed by bioinformatics scientists. This …

Abstract Background Bayesian Network (BN) is a powerful approach to reconstructing
genetic regulatory networks from gene expression data. However, expression data by itself …

As molecular biology continues to evolve in the direction of high-throughput collection of
data, it has become increasingly necessary to develop computational methods for analyzing …

As modeling becomes a more widespread practice in the life sciences and biomedical
sciences, researchers need reliable tools to calibrate models against ever more complex …

Systems Biology is now entering a mature phase in which the key issues are characterising
uncertainty and stochastic effects in mathematical models of biological systems. The area is …

In recent years there are a number of areas where graphical models have served
successfully in the process of understanding, formulating, and solving problems. Although …