Network stratification analysis for identifying function-specific network layers

doi:10.1039/c5mb00782h

	Network stratification analysis for identifying function-specific network layers
	Zhang, Chuanchao 1,2; Wang, Jiguang 2,3,4,5,6; Zhang, Chao 3,4; Liu, Juan 1; Xu, Dong 3,4; Chen, Luonan2,7,8
	2016
发表期刊	MOLECULAR BIOSYSTEMS (IF:3.336[JCR-2019],2.986[5-Year])
ISSN	1742-206X
卷号	12 期号:4 页码:1232-1240
发表状态	已发表
DOI	10.1039/c5mb00782h
摘要	A major challenge of systems biology is to capture the rewiring of biological functions (e.g. signaling pathways) in a molecular network. To address this problem, we proposed a novel computational framework, namely network stratification analysis (NetSA), to stratify the whole biological network into various function-specific network layers corresponding to particular functions (e.g. KEGG pathways), which transform the network analysis from the gene level to the functional level by integrating expression data, the gene/protein network and gene ontology information altogether. The application of NetSA in yeast and its comparison with a traditional network-partition both suggest that NetSA can more effectively reveal functional implications of network rewiring and extract significant phenotype-related biological processes. Furthermore, for time-series or stage-wise data, the function-specific network layer obtained by NetSA is also shown to be able to characterize the disease progression in a dynamic manner. In particular, when applying NetSA to hepatocellular carcinoma and type 1 diabetes, we can derive functional spectra regarding the progression of the disease, and capture active biological functions (i.e. active pathways) in different disease stages. The additional comparison between NetSA and SPIA illustrates again that NetSA could discover more complete biological functions during disease progression. Overall, NetSA provides a general framework to stratify a network into various layers of function-specific sub-networks, which can not only analyze a biological network on the functional level but also investigate gene rewiring patterns in biological processes.
收录类别	SCI
语种	英语
资助项目	Knowledge Innovation Program of SIBS of CAS[2013KIP218]
WOS研究方向	Biochemistry & Molecular Biology
WOS类目	Biochemistry & Molecular Biology
WOS记录号	WOS:000372612600018
出版者	ROYAL SOC CHEMISTRY
WOS关键词	PROTEIN INTERACTION NETWORKS ; GROWTH-FACTOR-I ; GENE ONTOLOGY ; BIOLOGICAL PATHWAYS ; DATABASE ; MODULES ; KNOWLEDGEBASE ; REACTOME ; CLASSIFICATION ; PREDICTION
原始文献类型	Article
引用统计	正在获取...
文献类型	期刊论文
条目标识符	https://kms.shanghaitech.edu.cn/handle/2MSLDSTB/2041
专题	生命科学与技术学院_特聘教授组_陈洛南组
通讯作者	Liu, Juan; Xu, Dong; Chen, Luonan
作者单位	1.Wuhan Univ, Sch Comp, Wuhan 430072, Peoples R China 2.Chinese Acad Sci, Key Lab Syst Biol, Innovat Ctr Cell Signaling Network, Inst Biochem & Cell Biol,Shanghai Inst Biol Sci, Shanghai 200233, Peoples R China 3.Univ Missouri, Dept Comp Sci, Columbia, MO 65211 USA 4.Univ Missouri, Christopher S Bond Life Sci Ctr, Columbia, MO 65211 USA 5.Columbia Univ, Dept Syst Biol, New York, NY 10032 USA 6.Columbia Univ, Dept Biomed Informat, New York, NY 10032 USA 7.ShanghaiTech Univ, Sch Life Sci & Technol, Shanghai 201210, Peoples R China 8.Univ Tokyo, Inst Ind Sci, Tokyo 1538505, Japan
通讯作者单位	生命科学与技术学院
推荐引用方式 GB/T 7714	Zhang, Chuanchao,Wang, Jiguang,Zhang, Chao,et al. Network stratification analysis for identifying function-specific network layers[J]. MOLECULAR BIOSYSTEMS,2016,12(4):1232-1240.
APA	Zhang, Chuanchao,Wang, Jiguang,Zhang, Chao,Liu, Juan,Xu, Dong,&Chen, Luonan.(2016).Network stratification analysis for identifying function-specific network layers.MOLECULAR BIOSYSTEMS,12(4),1232-1240.
MLA	Zhang, Chuanchao,et al."Network stratification analysis for identifying function-specific network layers".MOLECULAR BIOSYSTEMS 12.4(2016):1232-1240.