摘要
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.
出处
《应用科学学报》
CAS
CSCD
北大核心
2009年第3期282-287,共6页
Journal of Applied Sciences
基金
国家自然科学基金(No.30871341)
国家“863”高技术研究发展计划基金(No.2006AA02Z190)
上海市教委重点学科建设基金(No.J50101)
上海市重点学科基金(No.S30104)资助项目
关键词
遗传算法
禁忌搜索
双聚类
基因表达数据
genetic algorithm, tabu search, biclustering, gene expression data