基于禁忌搜索和遗传算法的智能化双聚类方法

Intelligentized Biclustering Based on Tabu Search and Genetic Algorithm

在基因表达数据中寻找重要双聚簇的难度随数据规模的增长而增长.该文讨论一种智能化的双聚类方法,充分利用禁忌搜索和遗传算法自身的爬山能力,很好地平衡了区域搜索和全局搜索的关系,并使输出结果不依赖于预先设定的阐值.实验表明,该方法具有很好的收敛性,并可发现比传统方法更好的双聚簇.

The degree of difficulty in finding significant biclusters in gene expression data grows with the increase of the size of the dataset. This paper presents an intelligent biclustering method which makes full use of the climbing ability of tabu search and genetic algorithm, balances relation between regional search and global search, and makes the results independent of a pre-defined threshold. Experiments show that the method has a better convergence property and can discover better biclusters than traditional methods.