Computational Methods for Protein Structure Prediction and Modeling. Volume 1, Basic Characterization

Volume one of this two volume sequence focuses on the basic characterization of known protein structures as well as structure prediction from protein sequence information. The 11 chapters provide an overview of the field, covering key topics in modeling, force fields, classification, computational m...

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Kolejni autorzy: Xu, Ying (Dyrektor wydawnictwa), Liang, Jie, 1964- (Dyrektor wydawnictwa), Xu, Dong, 1965- (Dyrektor wydawnictwa)
Format: Livre numérique
Język:Anglais
Wydane: New York, NY : Springer New York : Springer e-books [20..].
Cham : Springer Nature
Seria:BIOLOGICAL AND MEDICAL PHYSICS BIOMEDICAL ENGINEERING
Dostęp online:Accès sur la plateforme de l'éditeur
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Komentarz: Archives Springer e-books (Licence nationale)
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Edition sous un autre format:• Computational methods for protein structure prediction and modeling, Ying Xu, Dong Xu, and Jie Liang (eds.), New York, N.Y., Springer, 2007, 2 vol. (XX-394, 320 p.), Biological and medical physics, biomedical engineering, 0-387-33319-3
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505 1 |a A Historical Perspective and Overview of Protein Structure Prediction Empirical Force Fields Knowledge-Based Energy Functions for Computational Studies of Proteins Computational Methods for Domain Partitioning of Protein Structures Protein Structure Comparison and Classification Computation of Protein Geometry and Its Applications: Packing and Function Prediction Local Structure Prediction of Proteins Protein Contact Map Prediction Modeling Protein Aggregate Assembly and Structure Homology-Based Modeling of Protein Structure Modeling Protein Structures Based on Density Maps at Intermediate Resolutions 
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520 |a Volume one of this two volume sequence focuses on the basic characterization of known protein structures as well as structure prediction from protein sequence information. The 11 chapters provide an overview of the field, covering key topics in modeling, force fields, classification, computational methods, and struture prediction. Each chapter is a self contained review designed to cover (1) definition of the problem and an historical perspective, (2) mathematical or computational formulation of the problem, (3) computational methods and algorithms, (4) performance results, (5) existing software packages, and (6) strengths, pitfalls, challenges, and future research directions 
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