Preliminary results for GAMMI: Genetic algorithms for motif-module inference

Author

Gagne, David J. ; Congdon, Clare Bates

Author_Institution

Dept. of Comput. Sci., Univ. of Southern Maine, Portland, ME, USA

fYear

2012

fDate

10-15 June 2012

Firstpage

1

Lastpage

8

Abstract

We have developed GAMMI, an approach to the inference of cis-regulatory modules that employs an evolutionary search to identify modules conserved across a set of DNA sequences from different species. This paper describes the motivation and system design for GAMMI, and presents the results of initial tests of the system using artificial sequences with implanted artificial modules. Based on these preliminary tests, GAMMI appears to be a promising approach to the module inference problem.

Keywords

DNA; biology computing; evolutionary computation; genetic algorithms; inference mechanisms; search problems; DNA sequences; GAMMI; artificial modules; artificial sequences; cis-regulatory modules; evolutionary search; genetic algorithms for motif-module inference; module inference problem; Biological cells; Customer relationship management; DNA; Genetic algorithms; Laboratories; Libraries; Organisms; DNA motif inference; cis-regulatory modules; genetic algorithms;

fLanguage

English

Publisher

ieee

Conference_Titel

Evolutionary Computation (CEC), 2012 IEEE Congress on

Conference_Location

Brisbane, QLD

Print_ISBN

978-1-4673-1510-4

Electronic_ISBN

978-1-4673-1508-1

Type

conf

DOI

10.1109/CEC.2012.6252857

Filename

6252857