基于大量ChIP数据集的果蝇顺式调控模块的从头预测  

De novo prediction of cis-regulatory modules in D. melanogaster based on a large number of ChIP datasets

作　　者：李婷 张少强[1] LI Ting;ZHANG Shaoqiang(College of Computer and Information Engineering, Tianjin Normal University, Tianjin 300387, Chin)

机构地区：[1]天津师范大学计算机与信息工程学院,天津300387

出　　处：《天津师范大学学报（自然科学版）》2018年第2期73-76,共4页Journal of Tianjin Normal University：Natural Science Edition

基　　金：国家自然科学基金资助项目(61572358);天津市自然科学基金资助项目(16JCYBJC23600)

摘　　要：通过整合果蝇已有的ChIP数据集,采用模体发现算法FisherNet及高性能并行的模体聚类算法CLIMP对果蝇的顺式调控模块进行从头预测.与已知的顺式调控模块进行比对分析,结果表明该方法预测结果覆盖了数据集中已知顺式调控模块的82.93%,证明该方法具有一定的普适性.与较新的DePCRM算法进行比较,结果表明本算法在从头预测顺式调控模块上速度更快、精度更高.The ChIP datasets of D. melanogaster are integrated and used to predict the cis-regulatory modules by employing the motif discovery algorithm Fisher Net and the motif clustering algorithm CLIMP. By comparing with the known cis-regulatory modules,the prediction results recover 82.93% of the known cis-regulatory modules,which shows that the method has a certain universality. Comparing with the DePCRM algorithm,it is found that this algorithm is faster and more accurate than DePCRM for predicting the cis-regulatory modules.

关 键 词：ChIP数据集 果蝇 顺式调控模块 模体 FisherNet CLIMP 

分 类 号：Q78[生物学—分子生物学]