9. Integrative Protein Fold Recognition by Alignments and Machine Learning

  1. Huzefa Rangwala2 and
  2. George Karypis3
  1. Allison N. Tegge,
  2. Zheng Wang and
  3. Jianlin Cheng

Published Online: 7 SEP 2010

DOI: 10.1002/9780470882207.ch9

Introduction to Protein Structure Prediction: Methods and Algorithms

Introduction to Protein Structure Prediction: Methods and Algorithms

How to Cite

Tegge, A. N., Wang, Z. and Cheng, J. (2010) Integrative Protein Fold Recognition by Alignments and Machine Learning, in Introduction to Protein Structure Prediction: Methods and Algorithms (eds H. Rangwala and G. Karypis), John Wiley & Sons, Inc., Hoboken, NJ, USA. doi: 10.1002/9780470882207.ch9

Editor Information

  1. 2

    Department of Computer Science, George Mason University, Fairfax, VA 22030, USA

  2. 3

    Department of Computer Science, University of Minnesota Minneapolis, MN 55455, USA

Author Information

  1. Computer Science Department and Informatics Institute, University of Missouri, Columbia, MO 65211, USA

Publication History

  1. Published Online: 7 SEP 2010
  2. Published Print: 12 NOV 2010

Book Series:

  1. Wiley Series on Bioinformatics: Computational Techniques and Engineering

Book Series Editors:

  1. Yi Pan and
  2. Albert Zomaya

ISBN Information

Print ISBN: 9780470470596

Online ISBN: 9780470882207

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Keywords:

  • integrative protein fold recognition by alignments and machine learning - 3D structure prediction and template-based approach;
  • machine learning fold recognition methods - meta approach for fold recognition;
  • machine learning methods, more advanced useful features - needed for addressing fold recognition problem

Summary

This chapter contains sections titled:

  • Introduction

  • Alignment Fold Recognition Methods

  • Machine Learning Fold Recognition Methods

  • Conclusions

  • Acknowledgments

  • References