• Produktbild: Bayesian Methods in Structural Bioinformatics
  • Produktbild: Bayesian Methods in Structural Bioinformatics

Bayesian Methods in Structural Bioinformatics

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Beschreibung

Produktdetails

Einband

Taschenbuch

Erscheinungsdatum

13.04.2014

Abbildungen

XXII, 386 p.

Herausgeber

Thomas Hamelryck + weitere

Verlag

Springer Berlin

Seitenzahl

386

Maße (L/B/H)

23,5/15,5/2,3 cm

Gewicht

616 g

Auflage

1012

Sprache

Englisch

ISBN

978-3-642-43988-9

Beschreibung

Portrait


Thomas Hamelryck
is an associate professor at the Bioinformatics Center, University of Copenhagen. He completed his PhD in macromolecular crystallography at the Free University of Brussels (VUB). His research interests include the application of Bayesian machine learning methods and directional statistics to the inference of protein and RNA structure, based on sequence information or experimental data.



Kanti Mardia
(Senior Research Professor, University of Leeds) is a pioneering researcher and leader in modern statistical science, and is responsible for numerous groundbreaking developments; his monographs are highly acclaimed and he has played a lasting leadership role in interdisciplinary research. His most outstanding contributions lie in directional data analysis, shape analysis, spatial statistics, multivariate analysis, and protein bioinformatics.



Jesper Ferkinghoff-Borg
is an associate professor at the section for Biomedical Engineering, DTU-Electro, Technical University of Denmark (DTU), Copenhagen, where he heads the computational biophysics group. He received his PhD in theoretical physics from the Niels Bohr Institute at the University of Copenhagen. 

Produktdetails

Einband

Taschenbuch

Erscheinungsdatum

13.04.2014

Abbildungen

XXII, 386 p.

Herausgeber

Verlag

Springer Berlin

Seitenzahl

386

Maße (L/B/H)

23,5/15,5/2,3 cm

Gewicht

616 g

Auflage

1012

Sprache

Englisch

ISBN

978-3-642-43988-9

Herstelleradresse

Springer-Verlag GmbH
Tiergartenstr. 17
69121 Heidelberg
DE

Email: ProductSafety@springernature.com

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  • Produktbild: Bayesian Methods in Structural Bioinformatics
  • Produktbild: Bayesian Methods in Structural Bioinformatics

  • 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.