Computational Methods for Protein Structure Prediction and Modeling -
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Présentation Computational Methods For Protein Structure Prediction And Modeling Format Relié
- Livre Physique - Chimie
Résumé :
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.
Biographie:
Dr. Ying Xu is Regents-GRA Eminent Scholar and Professor at the University of Georgia. Dr. Dong Xu is the Director of the Digital Biology Laboratory at the University of Missouri-Columbia. Dr. Jie Liang is the Director for the Center for Bioinformatics at the University of Illinois at Chicago.
Sommaire:
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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