A Novel Method of Gene Regulatory Network Structure Inference from Gene Knock-Out Expression Data

论文摘要

Inferring Gene Regulatory Networks（GRNs） structure from gene expression data has been a challenging problem in systems biology. It is critical to identify complicated regulatory relationships among genes for understanding regulatory mechanisms in cells. Various methods based on information theory have been developed to infer GRNs. However, these methods introduce many redundant regulatory relationships in the network inference process due to external noise in the original data, topology sparseness in the network structure, and non-linear dependency among genes. Especially as the network size increases, the performance of these methods decreases dramatically. In this paper, a novel network structure inference method named Loc-PCA-CMI is proposed that first identifies local overlapped gene clusters, and then infers the local network structure for each cluster by a Path Consistency Algorithm based on Conditional Mutual Information（PCA-CMI）. The final structure of the GRN is denoted as dependence among genes by an ensemble of the obtained local network structures. Loc-PCA-CMI was evaluated on DREAM3 knock-out datasets, and its performance was compared to other information theorybased network inference methods including ARACNE, MRNET, PCA-CMI, and PCA-PMI. Experimental results demonstrate our novel method Loc-PCA-CMI outperforms the other four methods in DREAM3 datasets especially in size 50 and 100 networks.

论文目录

文章来源

类型: 期刊论文

作者: Xiang Chen,Min Li,Ruiqing Zheng,Siyu Zhao,Jianxin Wang,Fang-Xiang Wu,Yaohang Li

来源: Tsinghua Science and Technology 2019年04期

年度: 2019

分类: 工程科技Ⅱ辑,基础科学,信息科技

专业: 生物学,互联网技术

单位: the School of Computer Science and Engineering, Central South University,the Department of Mechanical Engineering and Division of Biomedical Engineering,University of Saskatchewan,the Department of Computer Science, Old Dominion University

基金: supported in part by the National Natural Science Foundation of China(Nos.61622213and 61732009),the 111 Project(No.B18059),the Hunan Provincial Science and Technology Program(No.2018WK4001)

分类号: Q811.4;TP393.02

页码: 446-454

总页数: 9

文件大小: 568K

下载量: 49

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