Preliminary Results for GAMI: A Genetic Algorithms Approach to Motif Inference

@article{Congdon2005PreliminaryRF,
  title={Preliminary Results for GAMI: A Genetic Algorithms Approach to Motif Inference},
  author={Clare Bates Congdon and Charles Fizer and Noah W. Smith and H. Rex Gaskins and Joseph C. Aman and Gerardo M. Nava and Carolyn J. Mattingly},
  journal={2005 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology},
  year={2005},
  pages={1-8}
}
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… CONTINUE READING
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