一种基于粗糙遗传算法的缩放模式双聚类分析方法

Biclustering Method for Detecting Scaling Patterns with Genetic Rough Algorithm

研究了基因表达数据的缩放模式发现问题,给出了一种缩放模式双聚类评价函数,并提出了一种基于粗糙遗传算法的双聚类分析方法。该方法先以启发式算法及随机方法生成初始种群,再基于粗糙遗传算法对种群进行迭代,以达到全局优化的目的。在Yeast数据集上进行的测试表明,该算法能对启发式算法的结果进行良好的修正。生物显著性分析表明所发现的缩放模式双聚类具有生物学意义。

This paper addressed the problem of detecting scaling patterns in gene expression data. A mean ratio residue as a merit function for Scaling patterns was presented. Based on the mean ratio residue a biclustering method was proposed under genetic rough framework. In this method, initial population is generated by Heuristic Rough Biclustering Algorithm as well as random choice. And then it adjust the seeds with Genetic Rough Algorithm. We tested this method on yeast expression data. The experimental results show that the Genetic Rough based method well improves the performance of heuristic algorithm and biclusters found on the yeast data are biologically significant using online GO Term Finder.