Chapter 14. Eukaryotic Promoter Detection Based on Word and Sequence Feature Selection and Combination

  1. Yan-Qing Zhang2 and
  2. Jagath C. Rajapakse3
  1. Xudong Xie,
  2. Shuanhu Wu and
  3. Hong Yan

Published Online: 21 APR 2008

DOI: 10.1002/9780470397428.ch14

Machine Learning in Bioinformatics

Machine Learning in Bioinformatics

How to Cite

Xie, X., Wu, S. and Yan, H. (2008) Eukaryotic Promoter Detection Based on Word and Sequence Feature Selection and Combination, in Machine Learning in Bioinformatics (eds Y.-Q. Zhang and J. C. Rajapakse), John Wiley & Sons, Inc., Hoboken, NJ, USA. doi: 10.1002/9780470397428.ch14

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. City University of Hong Kong, Hong Kong, China

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

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Keywords:

  • eukaryotic promoter detection;
  • promoter prediction based on adaboost algorithm;
  • computational prediction of eukaryotic promoters from nucleotide - problems in sequence analysis

Summary

This chapter contains sections titled:

  • Introduction

  • Promoter Prediction Based on Relative Entropy and Information Content

  • Promoter Prediction Based on the AdaBoost Algorithm

  • Experiment Results

  • Conclusions

  • Acknowledgments

  • References