Bayesian methods in structural bioinformatics - Info and Reading Options
By Thomas Hamelryck, K. V. Mardia and Jesper Ferkinghoff-Borg
"Bayesian methods in structural bioinformatics" was published by Springer in 2012 - Heidelberg, it has 385 pages and the language of the book is English.
“Bayesian methods in structural bioinformatics” Metadata:
- Title: ➤ Bayesian methods in structural bioinformatics
- Authors: Thomas HamelryckK. V. MardiaJesper Ferkinghoff-Borg
- Language: English
- Number of Pages: 385
- Publisher: Springer
- Publish Date: 2012
- Publish Location: Heidelberg
“Bayesian methods in structural bioinformatics” Subjects and Themes:
- Subjects: ➤ Statistical methods - Molecular Structure - Structural bioinformatics - Bayes Theorem - Statistical Models - Bayesian statistical decision theory - Bioinformatics - Molecular structure
Edition Specifications:
- Pagination: xxii, 385 p. :
Edition Identifiers:
- The Open Library ID: OL25363963M - OL16690834W
- Online Computer Library Center (OCLC) ID: 795366045
- Library of Congress Control Number (LCCN): 2012933773
- ISBN-13: 9783642272240 - 9783642272257
- ISBN-10: 364227224X - 3642272258
- All ISBNs: 364227224X - 3642272258 - 9783642272240 - 9783642272257
AI-generated Review of “Bayesian methods in structural bioinformatics”:
"Bayesian methods in structural bioinformatics" Table Of Contents:
- 1- Part 1.
- 2- Foundations --
- 3- An Overview of Bayesian Inference and Graphical Models -- Thomas Hamelryck
- 4- Monte Carlo Methods for Inference in High-Dimensional Systems -- Jesper Ferkinghoff-Borg -- Part 2.
- 5- Energy Functions for Protein Structure Prediction --
- 6- On the Physical Relevance and Statistical Interpretation of Knowledge-Based Potentials -- Mikael Borg, Thomas Hamelryck and Jesper Ferkinghoff-Borg
- 7- 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
- 8- Inferring Knowledge Based Potentials Using Contrastive Divergence -- Alexei A. Podtelezhnikov and David L. Wild -- Part 3.
- 9- Directional statistics for biomolecular structure --
- 10- Statistics of Bivariate von Mises Distributions -- Kanti V. Mardia and Jes Frellsen
- 11- Statistical Modelling and Simulation Using the Fisher-Bingham Distribution -- John T. Kent -- Part 4.
- 12- Shape Theory for Protein Structure Superposition --
- 13- Likelihood and Empirical Bayes Superposition of Multiple Macromolecular Structures -- Douglas L. Theobald
- 14- Bayesian Hierarchical Alignment Methods -- Kanti V. Mardia and Vysaul B. Nyirongo -- Part 5.
- 15- Graphical models for structure prediction --
- 16- Probabilistic Models of Local Biomolecular Structure and Their Applications -- Wouter Boomsma, Jes Frellsen and Thomas Hamelryck
- 17- Prediction of Low Energy Protein Side Chain Configurations Using Markov Random Fields -- Chen Yanover and Menachem Fromer -- Part 6.
- 18- Inferring Structure from Experimental Data --
- 19- Inferential Structure Determination from NMR Data -- Michael Habeck
- 20- Bayesian Methods in SAXS and SANS Structure Determination -- Steen Hansen.
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