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作 者:刘飞 王天丽[1] 高红艳 卫泽刚 张磊[1] 钱郁 LIU Fei;WANG Tian-li;GAO Hong-yan;WEI Ze-gang;ZHANG Lei;QIAN Yu(Institute of Physics and Optoelectronics Technology, Baoji University of Arts and Science, Baoji 721016, Shaanxi, China;Advanced Titanium Alloys and Functional Coatings Cooperative Innovation Center, Baoji University of Arts and Science, Baoji 721016, Shaanxi, China)
机构地区:[1]宝鸡文理学院物理与光电技术学院,陕西宝鸡721016 [2]宝鸡文理学院先进钛合金与功能涂层协同创新中心,陕西宝鸡721016
出 处:《宝鸡文理学院学报(自然科学版)》2021年第3期80-87,共8页Journal of Baoji University of Arts and Sciences(Natural Science Edition)
基 金:国家自然科学基金项目(11675001);陕西省科技计划项目(2018JM6099,2019JM-045);宝鸡市科技计划项目(2017JH2-18,2018JH-02)。
摘 要:目的提出一种利用共有基因模块构建大规模基因调控网络算法(Common Gene Modules Network,CGMN),有效降低传统基因调控网络构建基因节点规模较大的基因调控网络(包含几百个,甚至几千个基因节点)时时间复杂度过大的缺陷。方法CGMN算法从基因表达数据出发,采用6种常用聚类算法把基因表达模式相似的基因聚类成功能模块,找出6种聚类方法的共有模块,并将其作为功能模块基因节点,采用局部贝叶斯网络(Local Bayesian Network,LBN)算法构建功能模块基因-基因调控网络。结果与结论大规模细胞周期基因表达数据集上仿真实验结果表明,搜索共有模块压缩基因节点数目策略,能够有效降低大规模基因调控网络重构时间复杂度,且验证了CGMN算法构建大规模基因调控网络的有效性。Purposes—To propose a common gene modules network(CGMN)algorithm based on common gene modules,which can effectively reduce the time complexity of traditional gene regulatory network in constructing gene regulatory network with large-scale gene nodes(including hundreds or even thousands of gene nodes).Methods—Firstly,CGMN algorithm uses six gene clustering algorithms to cluster functional modules with similar gene expression patterns from the gene expression data.Then,the common modules discovered by six clustering methods are taken as the gene module nodes.In the end,local Bayesian network(LBN)algorithm is used to construct the gene-modules regulatory network.Results and Conclusion—Simulation results showed that the time complexity of reconstructing the large-scale gene regulatory network can be effectively reduced by searching the number of compressed gene nodes in common modules.CGMN algorithm can effectively construct large-scale gene regulatory network.
分 类 号:TP391[自动化与计算机技术—计算机应用技术]
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