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Bayesian Methods in Structural Bioinformatics

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Bayesian Methods in Structural Bioinformatics Synopsis

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 particular protein structure prediction, simulation, experimental structure determination and analysis). It focuses on statistical methods that have a clear interpretation in the framework of statistical physics, rather than ad hoc, black box methods based on neural networks or support vector machines. In addition, the emphasis is on methods that deal with biomolecular structure in atomic detail. The book is highly accessible, and only assumes background knowledge on protein structure, with a minimum of mathematical knowledge. Therefore, the book includes introductory chapters that contain a solid introduction to key topics such as Bayesian statistics and concepts in machine learning and statistical physics.

About This Edition

ISBN: 9783642439889
Publication date: 13th April 2014
Author: Thomas Hamelryck, Kanti Mardia, Jesper FerkinghoffBorg
Publisher: Springer an imprint of Springer Berlin Heidelberg
Format: Paperback
Pagination: 386 pages
Series: Statistics for Biology and Health
Genres: Probability and statistics
Biophysics
Computational biology / bioinformatics
Medical research