Bayesian Methods in Structural Bioinformatics

By Kanti V. Mardia, Thomas Hamelryck, Jesper Ferkinghoff-Borg

Book Overview

Part I Foundations: An Overview of Bayesian Inference and Graphical Models.- Monte Carlo Methods for Inferences in High-dimensional Systems.- Part II Energy Functions for Protein Structure Prediction: On the Physical Relevance and Statistical Interpretation of Knowledge based Potentials.- Statistical Machine Learning of Protein Energetics from Experimentally Observed Structures.- A Statistical View on the Reference Ratio Method.- Part III Directional Statistics and Shape Theory: Statistical Modelling and Simulation Using the Fisher-Bingham Distribution.- Statistics of Bivariate von Mises Distributions.- Bayesian Hierarchical Alignment Methods.- Likelihood and Empirical Bayes Superpositions of Multiple Macromolecular Structures.- Part IV Graphical models for structure prediction: Probabilistic Models of Local Biomolecular Structure and their Application in Structural Simulation.- Prediction of Low Energy Protein Side Chain Configurations Using Markov Random Fields.- Part V Inferring Structure from Experimental Data.- Inferential Structure Determination from NMR Data.- Bayesian Methods in SAXS and SANS Structure Determination.

• Format: Paperback
• Language: English
• ISBN: 3642439888
• ISBN13: 9783642439889
• Release Date: April 2014
• Publisher: Springer
• Length: 386 Pages
• Weight: 1.25 lbs.
• Dimensions: 0.8" x 6.1" x 9.2"