基于遗传算法的启动子序列多粒度结构分*析  

Multiple-Granular Structure Analysis of Promoters Based on Genetic Algorithm

作　　者：吴彦[1] 王立宏[2] 赵宪佳[3] 

机构地区：[1]青岛大学数学科学学院,青岛266071 [2]烟台大学计算机学院,烟台264005 [3]青岛大学国际学院,青岛266071

出　　处：《青岛大学学报（自然科学版）》2009年第2期11-14,共4页Journal of Qingdao University(Natural Science Edition)

基　　金：山东省自然科学基金(No.Y2008G08)

摘　　要：采用遗传算法对启动子序列数据集抽取不同长度的最优模糊子序列模式,以此分析启动子的结构。实验发现:适当调整子序列模式与样本序列的匹配程度阈值,可以发现局部频繁模式,除较长的TATA盒外还发现了其他一些模式,而在阈值较低时算法得到CpG岛。Genetic algorithm is employed to extract optimal fuzzy sub-sequence patterns with different lengths to find the structure of promoters. Experiments show that, some local frequent pattern can be found with respect to suitable threshold of match between sub-sequence and sample sequences. And then a long TATA box and some other new patterns are obtained. CpG island also appears frequently w. r. t low threshold value.

关 键 词：遗传算法 启动子 模糊子序列模式 

分 类 号：TP391.4[自动化与计算机技术—计算机应用技术]