Identifying network biomarkers based on protein-protein interactions and expression data

doi:10.1186/1755-8794-8-S2-S11

CSpace > 应用数学研究所

	Identifying network biomarkers based on protein-protein interactions and expression data
	Xin, Jingxue 1,2,5; Ren, Xianwen 3,4; Chen, Luonan 5; Wang, Yong1,2
	2015
发表期刊	BMC MEDICAL GENOMICS
ISSN	1755-8794
卷号	8 页码:11
摘要	Identifying effective biomarkers to battle complex diseases is an important but challenging task in biomedical research today. Molecular data of complex diseases is increasingly abundant due to the rapid advance of high throughput technologies. However, a great gap remains in identifying the massive molecular data to phenotypic changes, in particular, at a network level, i.e., a novel method for network biomarkers is in pressing need to accurately classify and diagnose diseases from molecular data and shed light on the mechanisms of disease pathogenesis. Rather than seeking differential genes at an individual-molecule level, here we propose a novel method for identifying network biomarkers based on protein-protein interaction affinity (PPIA), which identifies the differential interactions at a network level. Specifically, we firstly define PPIAs by estimating the concentrations of protein complexes based on the law of mass action upon gene expression data. Then we select a small and non-redundant group of protein-protein interactions and single proteins according to the PPIAs, that maximizes the discerning ability of cases from controls. This method is mathematically formulated as a linear programming, which can be efficiently solved and guarantees a globally optimal solution. Extensive results on experimental data in breast cancer demonstrate the effectiveness and efficiency of the proposed method for identifying network biomarkers, which not only can accurately distinguish the phenotypes but also provides significant biological insights at a network or pathway level. In addition, our method provides a new way to integrate static protein-protein interaction information with dynamical gene expression data.
DOI	10.1186/1755-8794-8-S2-S11
语种	英语
WOS研究方向	Genetics & Heredity
WOS类目	Genetics & Heredity
WOS记录号	WOS:000382997400012
出版者	BIOMED CENTRAL LTD
引用统计
文献类型	期刊论文
条目标识符	http://ir.amss.ac.cn/handle/2S8OKBNM/276
专题	应用数学研究所
通讯作者	Chen, Luonan
作者单位	1.Chinese Acad Sci, Acad Math & Syst Sci, Beijing 100190, Peoples R China 2.Chinese Acad Sci, Natl Ctr Math & Interdisciplinary Sci, Beijing 100190, Peoples R China 3.Chinese Acad Med Sci, Inst Pathogen Biol, MOH Key Lab Syst Biol Pathogens, Beijing 100730, Peoples R China 4.Peking Union Med Coll, Beijing 100730, Peoples R China 5.Chinese Acad Sci, Shanghai Inst Biol Sci, Key Lab Syst Biol, Shanghai 200233, Peoples R China
推荐引用方式 GB/T 7714	Xin, Jingxue,Ren, Xianwen,Chen, Luonan,et al. Identifying network biomarkers based on protein-protein interactions and expression data[J]. BMC MEDICAL GENOMICS,2015,8:11.
APA	Xin, Jingxue,Ren, Xianwen,Chen, Luonan,&Wang, Yong.(2015).Identifying network biomarkers based on protein-protein interactions and expression data.BMC MEDICAL GENOMICS,8,11.
MLA	Xin, Jingxue,et al."Identifying network biomarkers based on protein-protein interactions and expression data".BMC MEDICAL GENOMICS 8(2015):11.