小桶
计算机科学
微阵列分析技术
微阵列数据库
数据挖掘
构造(python库)
生物网络
微阵列
选择(遗传算法)
基因调控网络
网络分析
计算生物学
人工智能
基因本体论
基因
生物
基因表达
工程类
遗传学
电气工程
程序设计语言
作者
Shao Li,Lijiang Wu,Zhongqi Zhang
出处
期刊:Bioinformatics
[Oxford University Press]
日期:2006-07-04
卷期号:22 (17): 2143-2150
被引量:93
标识
DOI:10.1093/bioinformatics/btl363
摘要
Network reconstruction of biological entities is very important for understanding biological processes and the organizational principles of biological systems. This work focuses on integrating both the literatures and microarray gene-expression data, and a combined literature mining and microarray analysis (LMMA) approach is developed to construct gene networks of a specific biological system.In the LMMA approach, a global network is first constructed using the literature-based co-occurrence method. It is then refined using microarray data through a multivariate selection procedure. An application of LMMA to the angiogenesis is presented. Our result shows that the LMMA-based network is more reliable than the co-occurrence-based network in dealing with multiple levels of KEGG gene, KEGG Orthology and pathway.The LMMA program is available upon request.
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