Discovering cooperative biomarkers for heterogeneous complex disease diagnoses

doi:10.1093/bib/bbx090

CORC > 数学与系统科学研究院 > 中国科学院数学与系统科学研究院 > 应用数学研究所

	Discovering cooperative biomarkers for heterogeneous complex disease diagnoses
	Sun, Duanchen 1,2; Ren, Xianwen 3; Ari, Eszter 4,5; Korcsmaros, Tamas 6,7; Csermely, Peter 8; Wu, Ling-Yun2,9
刊名	BRIEFINGS IN BIOINFORMATICS
	2019
卷号	20 期号:1 页码:89-101
关键词	heterogeneous diseases cancer biomarker network-based cooperative biomarker gene expression
ISSN号	1467-5463
DOI	10.1093/bib/bbx090
英文摘要	Biomarkers with high reproducibility and accurate prediction performance can contribute to comprehending the underlying pathogenesis of related complex diseases and further facilitate disease diagnosis and therapy. Techniques integrating gene expression profiles and biological networks for the identification of network-based disease biomarkers are receiving increasing interest. The biomarkers for heterogeneous diseases often exhibit strong cooperative effects, which implies that a set of genes may achieve more accurate outcome prediction than any single gene. In this study, we evaluated various biomarker identification methods that consider gene cooperative effects implicitly or explicitly, and proposed the gene cooperation network to explicitly model the cooperative effects of gene combinations. The gene cooperation network-enhanced method, named as MarkRank, achieves superior performance compared with traditional biomarker identification methods in both simulation studies and real data sets. The biomarkers identified by MarkRank not only have a better prediction accuracy but also have stronger topological relationships in the biological network and exhibit high specificity associated with the related diseases. Furthermore, the top genes identified by MarkRank involve crucial biological processes of related diseases and give a good prioritization for known disease genes. In conclusion, MarkRank suggests that explicit modeling of gene cooperative effects can greatly improve biomarker identification for complex diseases, especially for diseases with high heterogeneity.
资助项目	Strategic Priority Research Program of the Chinese Academy of Sciences[XDB13040600] ; National Natural Science Foundation of China[11131009] ; National Natural Science Foundation of China[11631014] ; National Natural Science Foundation of China[91330114] ; National Natural Science Foundation of China[11661141019] ; Earlham Institute (Norwich, UK) ; Institute of Food Research (Norwich, UK) ; Hungarian National Research, Development and Innovation Office[K115378] ; Biotechnological and Biosciences Research Council, UK
WOS研究方向	Biochemistry & Molecular Biology ; Mathematical & Computational Biology
语种	英语
出版者	OXFORD UNIV PRESS
WOS记录号	WOS:000456736200009
内容类型	期刊论文
源URL	[http://ir.amss.ac.cn/handle/2S8OKBNM/32348]
专题	应用数学研究所
通讯作者	Wu, Ling-Yun
作者单位	1.Chinese Acad Sci, Acad Math & Syst Sci, Bioinformat, Beijing, Peoples R China 2.Univ Chinese Acad Sci, Sch Math Sci, Beijing, Peoples R China 3.Peking Univ, Biodynam Opt Imaging Ctr, Beijing, Peoples R China 4.Eotvos Lorand Univ, Dept Genet, Budapest, Hungary 5.Hungarian Acad Sci, Biol Res Ctr, Synthet & Syst Biol Unit, Szeged, Hungary 6.Inst Food Res, Norwich, Norfolk, England 7.Earlham Inst, Norwich, Norfolk, England 8.Semmelweis Univ, Dept Med Chem, Budapest, Hungary 9.Chinese Acad Sci, Acad Math & Syst Sci, Beijing, Peoples R China
推荐引用方式 GB/T 7714	Sun, Duanchen,Ren, Xianwen,Ari, Eszter,et al. Discovering cooperative biomarkers for heterogeneous complex disease diagnoses[J]. BRIEFINGS IN BIOINFORMATICS,2019,20(1):89-101.
APA	Sun, Duanchen,Ren, Xianwen,Ari, Eszter,Korcsmaros, Tamas,Csermely, Peter,&Wu, Ling-Yun.(2019).Discovering cooperative biomarkers for heterogeneous complex disease diagnoses.BRIEFINGS IN BIOINFORMATICS,20(1),89-101.
MLA	Sun, Duanchen,et al."Discovering cooperative biomarkers for heterogeneous complex disease diagnoses".BRIEFINGS IN BIOINFORMATICS 20.1(2019):89-101.