Synopses & Reviews
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.
Key Features
Addresses a broad interdisciplinary audience in biophysics and biochemistry, molecular and cell biology, computational biology, and bioinformatics
Provides a comprehensive overview of protein biophysics for both professionals and graduate students
Presents computational methods for all major aspects of protein structure analysis
Each chapter offers a self-contained review
Synopsis
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.
Synopsis
Volume One of this two-volume sequence focuses on the basic characterization of known protein structures, and structure prediction from protein sequence information. Eleven chapters survey of the field, covering key topics in modeling, force fields, classification, computational methods, and structure prediction. Each chapter is a self contained review covering definition of the problem and historical perspective; mathematical formulation; computational methods and algorithms; performance results; existing software; strengths, pitfalls, challenges, and future research.
About the Author
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.
Table of Contents
Modeling Protein Structures.- Empirical Force Fields.- Knowledge-based Energy Functions for Computational Studies of Proteins.