Chapter 13. Markov/Neural Model for Eukaryotic Promoter Recognition

  1. Yan-Qing Zhang2 and
  2. Jagath C. Rajapakse3
  1. Jagath C. Rajapakse3 and
  2. Sy Loi Ho1

Published Online: 21 APR 2008

DOI: 10.1002/9780470397428.ch13

Machine Learning in Bioinformatics

Machine Learning in Bioinformatics

How to Cite

Rajapakse, J. C. and Ho, S. L. (2008) Markov/Neural Model for Eukaryotic Promoter Recognition, in Machine Learning in Bioinformatics (eds Y.-Q. Zhang and J. C. Rajapakse), John Wiley & Sons, Inc., Hoboken, NJ, USA. doi: 10.1002/9780470397428.ch13

Editor Information

  1. 2

    Georgia State University, Atlanta, Georgia

  2. 3

    School of Computer Engineering, and The Bioinformatics Research Center, Nanyang Technological University, Nanyang, Singapore

Author Information

  1. 1

    Nanyang Technological University, Nanyang, Singapore

  2. 3

    School of Computer Engineering, and The Bioinformatics Research Center, Nanyang Technological University, Nanyang, Singapore

Publication History

  1. Published Online: 21 APR 2008
  2. Published Print: 12 NOV 2008

Book Series:

  1. Bioinformatics: Computational Techniques and Engineering

Book Series Editors:

  1. Professor Yi Pan and
  2. Professor Albert Y. Zomaya

ISBN Information

Print ISBN: 9780470116623

Online ISBN: 9780470397428

SEARCH

Keywords:

  • Markov/neural model for eukaryotic promoter recognition;
  • hybrid approach for identifying TSSs in RNA polymerase II promoters using Markov chains;
  • promising method for promoter recognition and higher-order Markov models framework

Summary

This chapter contains sections titled:

  • Introduction

  • Methods

  • Experiments and Results

  • Conclusion

  • References