Bayesian methods in structural bioinformatics

<p>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)....

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Bibliographic Details
Corporate Author: SpringerLink (Online service)
Other Authors: Mardia, Kanti, Ferkinghoff-Borg, Jesper, Hamelryck, Thomas
Format: eBook
Language:English
Published: Berlin, Heidelberg : Springer 2012.
Series:Statistics for Biology and Health,
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Table of Contents:
  • <p><b>Part I</b> Foundations: An Overview of Bayesian Inference and Graphical Models
  • Monte Carlo Methods for Inferences in High-dimensional Systems
  • <b>Part II</b> 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
  • <b>Part III</b> 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
  • <b>Part IV</b> 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
  • <b>Part V</b> Inferring Structure from Experimental Data
  • Inferential Structure Determination from NMR Data
  • Bayesian Methods in SAXS and SANS Structure Determination.</p>.