Preliminary results for GAMI: A genetic algorithms approach to motif inference

Clare Bates Congdon; Charles W. Fizer; Noah W. Smith; H. Rex Gaskins; Joseph Aman; Gerardo M. Nava; Carolyn Mattingly

doi:10.1109/cibcb.2005.1594904

Preliminary results for GAMI: A genetic algorithms approach to motif inference

Clare Bates Congdon, Charles W. Fizer, Noah W. Smith, H. Rex Gaskins, Joseph Aman, Gerardo M. Nava, Carolyn Mattingly

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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. GAMI is able to find a host of putative conserved patterns; possible approaches for validating the utility of the conserved regions are discussed.

Original language	English (US)
Title of host publication	Proceedings of the 2005 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology, CIBCB '05
Publisher	IEEE Computer Society
ISBN (Print)	0780393872, 9780780393875
DOIs	https://doi.org/10.1109/cibcb.2005.1594904
State	Published - 2005
Event	2005 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology, CIBCB '05 - La Jolla, CA, United States Duration: Nov 14 2005 → Nov 15 2005

Publication series

Name	Proceedings of the 2005 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology, CIBCB '05
Volume	2005

Other

Other	2005 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology, CIBCB '05
Country/Territory	United States
City	La Jolla, CA
Period	11/14/05 → 11/15/05

ASJC Scopus subject areas

General Engineering

Online availability

10.1109/cibcb.2005.1594904

Library availability

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Congdon, C. B., Fizer, C. W., Smith, N. W., Gaskins, H. R., Aman, J., Nava, G. M., & Mattingly, C. (2005). Preliminary results for GAMI: A genetic algorithms approach to motif inference. In Proceedings of the 2005 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology, CIBCB '05 Article 1594904 (Proceedings of the 2005 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology, CIBCB '05; Vol. 2005). IEEE Computer Society. https://doi.org/10.1109/cibcb.2005.1594904

Preliminary results for GAMI: A genetic algorithms approach to motif inference. / Congdon, Clare Bates; Fizer, Charles W.; Smith, Noah W. et al.
Proceedings of the 2005 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology, CIBCB '05. IEEE Computer Society, 2005. 1594904 (Proceedings of the 2005 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology, CIBCB '05; Vol. 2005).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Congdon, CB, Fizer, CW, Smith, NW, Gaskins, HR, Aman, J, Nava, GM & Mattingly, C 2005, Preliminary results for GAMI: A genetic algorithms approach to motif inference. in Proceedings of the 2005 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology, CIBCB '05., 1594904, Proceedings of the 2005 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology, CIBCB '05, vol. 2005, IEEE Computer Society, 2005 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology, CIBCB '05, La Jolla, CA, United States, 11/14/05. https://doi.org/10.1109/cibcb.2005.1594904

Congdon CB, Fizer CW, Smith NW, Gaskins HR, Aman J, Nava GM et al. Preliminary results for GAMI: A genetic algorithms approach to motif inference. In Proceedings of the 2005 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology, CIBCB '05. IEEE Computer Society. 2005. 1594904. (Proceedings of the 2005 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology, CIBCB '05). doi: 10.1109/cibcb.2005.1594904

Congdon, Clare Bates ; Fizer, Charles W. ; Smith, Noah W. et al. / Preliminary 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 '05. IEEE Computer Society, 2005. (Proceedings of the 2005 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology, CIBCB '05).

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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. GAMI is able to find a host of putative conserved patterns; possible approaches for validating the utility of the conserved regions are discussed.",

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Preliminary results for GAMI: A genetic algorithms approach to motif inference

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