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Contribution to Book
reliminary Results for GAMI: A Genetic Algorithms Approach to Motif Inference
Proceedings of the 2005 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology (CIBCB-2005) (2005)
  • Clare Bates Congdon, University of Southern Maine
  • C. W. Fizer
  • N. W. Smith
  • H. R. Gaskins
  • Joseph Aman
  • G M. Nava
  • Carolyn Mattingly
Abstract

We have developed GAMI, an approach to motif inference that uses a genetic algorithms search and is designed specifically to work with divergent species and possibly long nucleotide sequences. The system design reduces the size of the search space as compared to typical window-location approaches for motif inference. This paper describes the motivation and system design for GAMI, discusses how we have designed the search space and compares this to the search space of other approaches, and presents initial results with data from the literature and from novel tasks.

Keywords
  • Bioinformatics,
  • Genetic Algorithms,
  • Genomics,
  • Inference Algorithms
Publication Date
November, 2005
Publisher
IEEE
Publisher Statement
Copyright IEEE 2005 all rights reserved Digital Object Identifier : 10.1109/CIBCB.2005.1594904
Citation Information
Clare Bates Congdon, C. W. Fizer, N. W. Smith, H. R. Gaskins, et al.. "reliminary Results for GAMI: A Genetic Algorithms Approach to Motif Inference" Picataway, N.J.Proceedings of the 2005 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology (CIBCB-2005) (2005)
Available at: http://works.bepress.com/clare_congdon/5/