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Bayesian Methods in Structural Bioinformatics
Apr 13, 2014, Springer
paperback
3642439888 9783642439889
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Book Details
Table of 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.
Edition Notes
Includes bibliographical references (p. 343-376) and index.
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