Bayesian Methods in Structural Bioinformatics
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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.
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Details
- ISBN-13: 9783642272240
- ISBN-10: 364227224X
- Publisher: Springer
- Publish Date: March 2012
- Dimensions: 9.2 x 6.3 x 1 inches
- Shipping Weight: 1.55 pounds
- Page Count: 386
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