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| A Novel Biclustering Algorithm and Its Application in Gene Expression Profiles |
| Wei Shen, Guixia Liu, Ming Zheng, Zhangxu Li, Yi Zhong, Jianan Wu, Chunguang Zhou |
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Abstract In order to propose a novel biclustering algorithm and to cluster
gene expression data, this paper improved the residue function of
the biclustering algorithm. The improved function can be more
appropriate used for stochastic heuristic searching algorithm. The
parallel genetic algorithm was firstly introduced to the of the
biclustering optimization algorithm. Hence this method can prevent
local convergence in the optimal algorithm in a great extent, and
make the probability of approaching the global convergence bigger.
The algorithm used the Yeast Saccharomyces cerevisiae cell cycle
gene expression profile from the data Spellman used in his own
experiment in Stanford database to bicluster. And we compared our
algorithm with traditional genetic algorithms in biclustering. The
efficiency of this algorithm was proved.
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