Title :
GAVis: a Tool for Visualization and Control of Genetic Algorithms for -omic Data Analysis
Author :
Stokes, Todd H. ; Phan, John H. ; Feng, Weimin M. ; Tuteja, Gaurav ; Wang, May D.
Author_Institution :
Wallace H. Coulter Biomed. Eng. Dept., Georgia Inst. of Technol., Atlanta, GA
fDate :
6/27/1905 12:00:00 AM
Abstract :
A visualization and steering application, GAVis, has been developed to aid in understanding the behavior of and guiding the convergence of genetic algorithms running in parallel over long time periods. When classification techniques such as support vector machines (SVMs) paired with complete leave-one-out validation are used as a fitness function for identification of markers in -omic data, the time to complete one generation can exceed an hour on modern high-performance computing clusters. Separate solution populations on "islands" can help maintain a more diverse solution space and conveniently map to compute nodes on a cluster. Adjustments can be made at runtime to speed the convergence of genetic algorithms by stimulating lagging island populations with migrations of high-performing individuals or by selectively increasing mutation rates
Keywords :
genetic algorithms; medical diagnostic computing; support vector machines; -omic data analysis; GAVis; complete leave-one-out validation; genetic algorithms; lagging island populations; mutation rates; support vector machines; Bioinformatics; Biomedical engineering; Data analysis; Data visualization; Diseases; Genetic algorithms; Genetic mutations; Runtime; Support vector machine classification; Support vector machines;
Conference_Titel :
Engineering in Medicine and Biology Society, 2005. IEEE-EMBS 2005. 27th Annual International Conference of the
Conference_Location :
Shanghai
Print_ISBN :
0-7803-8741-4
DOI :
10.1109/IEMBS.2005.1617069
