DocumentCode
2767614
Title
Using genetic algorithms for the inference of motifs that are represented in only a subset of sequences of interest
Author
Thompson, Jeffrey A. ; Congdon, Clare Bates
Author_Institution
Dept. of Comput. Sci., Univ. of Southern Maine, Portland, ME, USA
fYear
2011
fDate
12-15 Nov. 2011
Firstpage
1005
Lastpage
1005
Abstract
In this work, we present GAMID, and extension of GAMI. GAMID is designed to be used for motif inference in noncoding DNA for co-expressed genes or for divergent species. In these cases, we would like to allow the inferred motif to be present in only a subset of the input data. This paper describes the approach and presents preliminary results.
Keywords
DNA; genetic algorithms; genetics; molecular biophysics; DNA noncoding; GAMID; Genetic Algorithms; coexpressed genes; divergent species; input data; motif inference; Bioinformatics; Conferences; DNA; Economics; Evolutionary computation; Genetic algorithms; Robustness; DNA motif inference; genetic algorithms; motif;
fLanguage
English
Publisher
ieee
Conference_Titel
Bioinformatics and Biomedicine Workshops (BIBMW), 2011 IEEE International Conference on
Conference_Location
Atlanta, GA
Print_ISBN
978-1-4577-1612-6
Type
conf
DOI
10.1109/BIBMW.2011.6112539
Filename
6112539
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