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
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;
Conference_Titel :
Bioinformatics and Biomedicine Workshops (BIBMW), 2011 IEEE International Conference on
Conference_Location :
Atlanta, GA
Print_ISBN :
978-1-4577-1612-6
DOI :
10.1109/BIBMW.2011.6112539
