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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Other Authors: | , , |
Format: | eBook |
Language: | English |
Published: |
Berlin, Heidelberg :
Springer
2012.
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Series: | Statistics for Biology and Health,
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Subjects: | |
Online Access: | Click here to view the full text content |
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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>.