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Introduction to Protein Structure Prediction Methods and Algorithms 1st Edition by Huzefa Rangwala, George Karypis ISBN 0470470593 978-0470470596

  • SKU: BELL-2160732
Introduction to Protein Structure Prediction Methods and Algorithms 1st Edition by Huzefa Rangwala, George Karypis ISBN 0470470593 978-0470470596
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Introduction to Protein Structure Prediction Methods and Algorithms 1st Edition by Huzefa Rangwala, George Karypis ISBN 0470470593 978-0470470596 instant download after payment.

Publisher: Wiley
File Extension: PDF
File size: 28.16 MB
Pages: 522
Author: Huzefa Rangwala, George Karypis
ISBN: 9780470470596, 0470470593
Language: English
Year: 2010

Product desciption

Introduction to Protein Structure Prediction Methods and Algorithms 1st Edition by Huzefa Rangwala, George Karypis ISBN 0470470593 978-0470470596 by Huzefa Rangwala, George Karypis 9780470470596, 0470470593 instant download after payment.

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Product details:

ISBN 10: 0470470593

ISBN 13: 978-0470470596 

Author: Huzefa Rangwala, George Karypis 

A look at the methods and algorithms used to predict protein structure

A thorough knowledge of the function and structure of proteins is critical for the advancement of biology and the life sciences as well as the development of better drugs, higher-yield crops, and even synthetic bio-fuels. To that end, this reference sheds light on the methods used for protein structure prediction and reveals the key applications of modeled structures. This indispensable book covers the applications of modeled protein structures and unravels the relationship between pure sequence information and three-dimensional structure, which continues to be one of the greatest challenges in molecular biology.

With this resource, readers will find an all-encompassing examination of the problems, methods, tools, servers, databases, and applications of protein structure prediction and they will acquire unique insight into the future applications of the modeled protein structures. The book begins with a thorough introduction to the protein structure prediction problem and is divided into four themes: a background on structure prediction, the prediction of structural elements, tertiary structure prediction, and functional insights. Within those four sections, the following topics are covered:

  • Databases and resources that are commonly used for protein structure prediction
  • The structure prediction flagship assessment (CASP) and the protein structure initiative (PSI)
  • Definitions of recurring substructures and the computational approaches used for solving sequence problems
  • Difficulties with contact map prediction and how sophisticated machine learning methods can solve those problems
  • Structure prediction methods that rely on homology modeling, threading, and fragment assembly
  • Hybrid methods that achieve high-resolution protein structures
  • Parts of the protein structure that may be conserved and used to interact with other biomolecules
  • How the loop prediction problem can be used for refinement of the modeled structures
  • The computational model that detects the differences between protein structure and its modeled mutant

Whether working in the field of bioinformatics or molecular biology research or taking courses in protein modeling, readers will find the content in this book invaluable.

Table of contents:

  1. Introduction to Protein Structure Prediction

  2. CASP: A Driving Force in Protein Structure Modeling

  3. The Protein Structure Initiative

  4. Prediction of One-Dimensional Structural Properties Of Proteins by Integrated Neural Networks

  5. Local Structure Alphabets

  6. Shedding Light on Transmembrane Topology

  7. Contact Map Prediction by Machine Learning

  8. A Survey of Remote Homology Detection and Fold Recognition Methods

  9. Integrative Protein Fold Recognition by Alignments and Machine Learning

  10. Tasser-Based Protein Structure Prediction

  11. Composite Approaches to Protein Tertiary Structure Prediction: A Case-Study by I-Tasser

  12. Hybrid Methods for Protein Structure Prediction

  13. Modeling Loops in Protein Structures

  14. Model Quality Assessment Using a Statistical Program that Adopts a Side Chain Environment Viewpoint

  15. Model Quality Prediction

  16. Ligand-Binding Residue Prediction

  17. Modeling and Validation of Transmembrane Protein Structures

  18. Structure-Based Machine Learning Models for Computational Mutagenesis

  19. Conformational Search for the Protein Native State

  20. Modeling Mutations in Proteins Using Medusa and Discrete Molecule Dynamics

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Tags: Huzefa Rangwala, George Karypis, Introduction, Protein, Structure, Prediction, Methods, Algorithms

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