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Title Bayesian methods in structural bioinformatics / Thomas Hamelryck, Kanti Mardia, Jesper Ferkinghoff-Borg, editors
Published Berlin ; New York : Springer, ©2012

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Description 1 online resource (xxii, 385 pages) : portraits
Series Statistics for biology and health, 1431-8776
Statistics for biology and health.
Contents Part 1. Foundations -- An Overview of Bayesian Inference and Graphical Models / Thomas Hamelryck -- Monte Carlo Methods for Inference in High-Dimensional Systems / Jesper Ferkinghoff-Borg -- Part 2. Energy Functions for Protein Structure Prediction -- On the Physical Relevance and Statistical Interpretation of Knowledge-Based Potentials / Mikael Borg, Thomas Hamelryck and Jesper Ferkinghoff-Borg -- Towards a General Probabilistic Model of Protein Structure: The Reference Ratio Method / Jes Frellsen, Kanti V. Mardia, Mikael Borg, Jesper Ferkinghoff-Borg and Thomas Hamelryck -- Inferring Knowledge Based Potentials Using Contrastive Divergence / Alexei A. Podtelezhnikov and David L. Wild -- Part 3. Directional statistics for biomolecular structure -- Statistics of Bivariate von Mises Distributions / Kanti V. Mardia and Jes Frellsen -- Statistical Modelling and Simulation Using the Fisher-Bingham Distribution / John T. Kent -- Part 4. Shape Theory for Protein Structure Superposition -- Likelihood and Empirical Bayes Superposition of Multiple Macromolecular Structures / Douglas L. Theobald -- Bayesian Hierarchical Alignment Methods / Kanti V. Mardia and Vysaul B. Nyirongo -- Part 5. Graphical models for structure prediction -- Probabilistic Models of Local Biomolecular Structure and Their Applications / Wouter Boomsma, Jes Frellsen and Thomas Hamelryck -- Prediction of Low Energy Protein Side Chain Configurations Using Markov Random Fields / Chen Yanover and Menachem Fromer -- Part 6. Inferring Structure from Experimental Data -- Inferential Structure Determination from NMR Data / Michael Habeck -- Bayesian Methods in SAXS and SANS Structure Determination / Steen Hansen
Summary 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
Analysis Statistics
Medicine
Bioinformatics
Statistics for Life Sciences, Medicine, Health Sciences
Molecular Medicine
Biophysics and Biological Physics
Mathematical and Computational Biology
Computational Biology/Bioinformatics
Bibliography Includes bibliographical references and index
Notes English
Subject Structural bioinformatics -- Statistical methods
Computational Biology -- statistics & numerical data
bioinformatics
SCIENCE -- Life Sciences -- Biochemistry.
Estadística bayesiana
Bayesian statistical decision theory
Structural bioinformatics
Form Electronic book
Author Hamelryck, Thomas.
Mardia, K. V.
Ferkinghoff-Borg, Jesper.
LC no. 2012933773
ISBN 9783642272257
3642272258
364227224X
9783642272240