单基因扰动实验的并行自适应灰关联聚类算法研究  

A Parallel Adaptive Algorithm of Parameter Grey Gelation Cluster Analysis for the Single-gene Disturbed Experiment

作　　者：张轶雯[1,2] 何冰[1] 谢江[1,2] 金翊[1] 张武[1,2] 

机构地区：[1]上海大学计算机工程与科学学院,上海200072 [2]上海大学系统生物技术研究所,上海200444

出　　处：《微电子学与计算机》2009年第9期107-109,共3页Microelectronics & Computer

基　　金：教育部高等学校博士学科点专项科研基金(200802800007);上海市重点学科建设项目资助基金(J50103)

摘　　要：为有效进行大数据量单基因扰动的生物学实验,基于自适应灰关联聚类算法,提出一个并行自适应灰关联聚类算法,并行处理大数据量的单基因扰动,并建立相应的基因调控网络.计算结果表明,该并行算法具有很好的并行性能.To efficiently process large amount of data for single-gene disturbed experiment, which spends the longer time cycle and the higher cost, a parallel adaptive algorithm of parameter grey relation duster analysis is developed in this paper. The algorithm can deal with massive data for single-gene disturbance, and establish the gene regulatory network. Compared with sequential computing, numerical results of parallel computing show higher performance of both computing scale and time.

关 键 词：并行算法 基因扰动 灰关联聚类 

分 类 号：TP339[自动化与计算机技术—计算机系统结构] TP338.6[自动化与计算机技术—计算机科学与技术]