DocumentCode
3048147
Title
Biclustering of Gene Expression Data Using PSO-GA Hybrid
Author
Xie, Baiyi ; Chen, Shihong ; Liu, Feng
Author_Institution
Comput. Sch., Wuhan Univ., Wuhan
fYear
2007
fDate
6-8 July 2007
Firstpage
302
Lastpage
305
Abstract
The biclustering of gene expression data is an important technology for biologists and the biclustering problem is proven to be NP-hard. In this paper, a hybrid evolutionary optimization algorithm based on particle swarm and Genetic algorithms is presented to solve the biclustering problem. Additionally, this paper gives a comparison between hybrid algorithm, GA, and PSO. Experiments show that our method can beat other methods.
Keywords
cellular biophysics; genetic algorithms; genetics; molecular biophysics; optimisation; PSO-GA hybrid; biclustering; gene expression; genetic algorithms; hybrid evolutionary optimization algorithm; particle swarm; Biology computing; Clustering algorithms; DNA; Evolutionary computation; Gene expression; Genetic algorithms; Optimization methods; Particle swarm optimization; Rail transportation; Simulated annealing;
fLanguage
English
Publisher
ieee
Conference_Titel
Bioinformatics and Biomedical Engineering, 2007. ICBBE 2007. The 1st International Conference on
Conference_Location
Wuhan
Print_ISBN
1-4244-1120-3
Type
conf
DOI
10.1109/ICBBE.2007.81
Filename
4272565
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