in this research, a new algorithm named fuzzy correlation coefficient was brought up to construct gene regulatory network 我们在已有的三种相关系数的基础上,借鉴模糊隶属度思想,提出一种新的模糊相关基因表达调控网络构建算法。
fuzzy correlation coefficient and three other existed methods ( pearson, spearman and information entropy correlation coefficient ) were used to analyze three microarray data sets which were about human gene expression during the development of cns in embryonic period . to accomplish the construction of gene expression regulatory network, a program was completed with matlab package 利用matlab工作平台,进行程序设计,研制一种新的构建基因表达调控网络的软件,并将已有的三种相关系数和模糊相关系数应用到人类胚胎期中枢神经系统发育过程基因表达数据中,建立调控网络,并对结果进行分析和比较。
traditional grouping method could not use all attributes of entity and fuzzy correlation space based approach needed more match computation . fuzzy grouping method added two new techniques based on the fuzzy correlation space approach : fuzzy consistent relation based weight distribution and grid based preprocessing 由于传统的分组方法不能充分利用实体所有的属性,而基于模糊关联空间的分组方法需要过多的运算量,本文提出一种模糊分组方法,该分组方法在基于模糊关联空间方法的基础上加入基于模糊一致性的权值分配方法和基于格子的预处理分组方法。
traditional grouping method could not use all attributes of entity and fuzzy correlation space based approach needed more match computation . fuzzy grouping method added two new techniques based on the fuzzy correlation space approach : fuzzy consistent relation based weight distribution and grid based preprocessing 由于传统的分组方法不能充分利用实体所有的属性,而基于模糊关联空间的分组方法需要过多的运算量,本文提出一种模糊分组方法,该分组方法在基于模糊关联空间方法的基础上加入基于模糊一致性的权值分配方法和基于格子的预处理分组方法。