1. Current Methods for Protein Secondary-Structure Prediction Based on Support Vector Machines

  1. Xiaohua Hu3 and
  2. Yi Pan4
  1. Hae-Jin Hu4,
  2. Robert W. Harrison1,
  3. Phang C. Tai2 and
  4. Yi Pan4

Published Online: 23 MAY 2007

DOI: 10.1002/9780470124642.ch1

Knowledge Discovery in Bioinformatics: Techniques, Methods, and Applications

Knowledge Discovery in Bioinformatics: Techniques, Methods, and Applications

How to Cite

Hu, H.-J., Harrison, R. W., Tai, P. C. and Pan, Y. (2007) Current Methods for Protein Secondary-Structure Prediction Based on Support Vector Machines, in Knowledge Discovery in Bioinformatics: Techniques, Methods, and Applications (eds X. Hu and Y. Pan), John Wiley & Sons, Inc., Hoboken, NJ, USA. doi: 10.1002/9780470124642.ch1

Editor Information

  1. 3

    College of Information Science and Technology, Drexel University, Philadelphia, PA 19104, USA

  2. 4

    Department of Computer Science, Georgia State University, Atlanta, GA 30302-4110, USA

Author Information

  1. 1

    Department of Computer Science and Department of Biology, Georgia State University, Atlanta, GA 30302-4110, USA

  2. 2

    Department of Biology, Georgia State University, Atlanta, GA 30302-4110, USA

  3. 4

    Department of Computer Science, Georgia State University, Atlanta, GA 30302-4110, USA

Publication History

  1. Published Online: 23 MAY 2007
  2. Published Print: 25 MAY 2007

ISBN Information

Print ISBN: 9780471777960

Online ISBN: 9780470124642

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Keywords:

  • protein secondary-structure prediction;
  • support vector machine (SVM) method;
  • SVM schemes and secondary-structure prediction

Summary

This chapter contains sections titled:

  • Traditional Methods

  • Support Vector Machine Method

  • Performance Comparison of SVM Methods

  • Discussion and Conclusions

  • References