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An Evaluation of Information Content as a Metric for the Inference of Putative Conserved Noncoding Regions in DNA Sequences Using a Genetic Algorithms Approach
IEEE-ACM Transactions on Computational Biology and Bioinformatics (2008)
  • Clare Bates Congdon, University of Southern Maine
  • Joseph C. Aman
  • Gerado M. Nava, University of Illinois at Urbana-Champaign
  • H. Rex Gaskins, University of Illinois at Urbana-Champaign
  • Carolyn J. Mattingly
Abstract

In this work, we compare GAMI's performance when run with its original fitness function (a simple count of the number of matches) and when run with information content (IC), as well as several variations on these metrics.

Keywords
  • Evolutionary Computing; Genetic Algorithms; Biology; Genetics
Publication Date
January, 2008
Publisher Statement
copyright 2008 IEEE Computer Society
Citation Information
Clare Bates Congdon, Joseph C. Aman, Gerado M. Nava, H. Rex Gaskins, et al.. "An Evaluation of Information Content as a Metric for the Inference of Putative Conserved Noncoding Regions in DNA Sequences Using a Genetic Algorithms Approach" IEEE-ACM Transactions on Computational Biology and Bioinformatics Vol. 5 Iss. 1 (2008)
Available at: http://works.bepress.com/clare_congdon/3/