14. Identification of Transmembrane Proteins Using Variants of the Self-Organizing Feature Map Algorithm

  1. Xiaohua Hu4 and
  2. Yi Pan5
  1. Mary Qu Yang1,
  2. Jack Y. Yang2 and
  3. Craig W. Codrington3

Published Online: 23 MAY 2007

DOI: 10.1002/9780470124642.ch14

Knowledge Discovery in Bioinformatics: Techniques, Methods, and Applications

Knowledge Discovery in Bioinformatics: Techniques, Methods, and Applications

How to Cite

Yang, M. Q., Yang, J. Y. and Codrington, C. W. (2007) Identification of Transmembrane Proteins Using Variants of the Self-Organizing Feature Map Algorithm, 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.ch14

Editor Information

  1. 4

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

  2. 5

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

Author Information

  1. 1

    National Human Genome Research Institute, National Institutes of Health, Bethesda, MD 20892, USA

  2. 2

    Harvard Medical School, Harvard University, Boston, MA 02115, USA

  3. 3

    Department of Physics, Purdue University, West Lafayette, IN 47907, 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:

  • transmembrane protein identification;
  • self-organized global ranking (SOGR) algorithm;
  • SOGR-I and SOGR-IB classifiers

Summary

This chapter contains sections titled:

  • Physiochemical Analysis of Proteins

  • Variants of the SOM Algorithm

  • Results

  • Discussion and Conclusions

  • References