Bayesian Methods in Structural Bioinformatics

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). It focus...

Πλήρης περιγραφή

Λεπτομέρειες βιβλιογραφικής εγγραφής
Συγγραφή απο Οργανισμό/Αρχή: SpringerLink (Online service)
Άλλοι συγγραφείς: Hamelryck, Thomas (Επιμελητής έκδοσης), Mardia, Kanti (Επιμελητής έκδοσης), Ferkinghoff-Borg, Jesper (Επιμελητής έκδοσης)
Μορφή: Ηλεκτρονική πηγή Ηλ. βιβλίο
Γλώσσα:English
Έκδοση: Berlin, Heidelberg : Springer Berlin Heidelberg, 2012.
Σειρά:Statistics for Biology and Health,
Θέματα:
Διαθέσιμο Online:Full Text via HEAL-Link
Πίνακας περιεχομένων:
  • 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.