Bayesian methods in structural bioinformatics
By: Thomas Hamelryck, Kanti Mardia, Jesper Ferkinghoff-Borg, editors
Series: Statistics for biology and health; Statistics for biology and health
Publisher: Springer
Published: 2012
Place of publication: Heidelberg; New York
Language: eng
Number of pages: 385
ISBN-13: 9783642272240; 9783642272257
Subjects: Statistical methods; Molecular Structure; Structural bioinformatics; Bayes Theorem; Statistical Models
Notes: Includes bibliographical references (p. 343-376) and index.
Table of contents: title: Part 1.; title: Foundations --; title: An Overview of Bayesian Inference and Graphical Models  -- Thomas Hamelryck; title: Monte Carlo Methods for Inference in High-Dimensional Systems  -- Jesper Ferkinghoff-Borg -- Part 2.; title: Energy Functions for Protein Structure Prediction --; title: On the Physical Relevance and Statistical Interpretation of Knowledge-Based Potentials  -- Mikael Borg, Thomas Hamelryck and Jesper Ferkinghoff-Borg; title: 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; title: Inferring Knowledge Based Potentials Using Contrastive Divergence  -- Alexei A. Podtelezhnikov and David L. Wild -- Part 3.; title: Directional statistics for biomolecular structure --; title: Statistics of Bivariate von Mises Distributions  -- Kanti V. Mardia and Jes Frellsen; title: Statistical Modelling and Simulation Using the Fisher-Bingham Distribution  -- John T. Kent -- Part 4.; title: Shape Theory for Protein Structure Superposition --; title: Likelihood and Empirical Bayes Superposition of Multiple Macromolecular Structures  -- Douglas L. Theobald; title: Bayesian Hierarchical Alignment Methods  -- Kanti V. Mardia and Vysaul B. Nyirongo -- Part 5.; title: Graphical models for structure prediction --; title: Probabilistic Models of Local Biomolecular Structure and Their Applications  -- Wouter Boomsma, Jes Frellsen and Thomas Hamelryck; title: Prediction of Low Energy Protein Side Chain Configurations Using Markov Random Fields  -- Chen Yanover and Menachem Fromer -- Part 6.; title: Inferring Structure from Experimental Data --; title: Inferential Structure Determination from NMR Data  -- Michael Habeck; title: Bayesian Methods in SAXS and SANS Structure Determination -- Steen Hansen.