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Discovering cooperative biomarkers for heterogeneous complex disease diagnoses
Sun, Duanchen1,2; Ren, Xianwen3; Ari, Eszter4,5; Korcsmaros, Tamas6,7; Csermely, Peter8; Wu, Ling-Yun2,9
2019
Source PublicationBRIEFINGS IN BIOINFORMATICS
ISSN1467-5463
Volume20Issue:1Pages:89-101
AbstractBiomarkers 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.
Keywordheterogeneous diseases cancer biomarker network-based cooperative biomarker gene expression
DOI10.1093/bib/bbx090
Language英语
Funding ProjectStrategic 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 Research AreaBiochemistry & Molecular Biology ; Mathematical & Computational Biology
WOS SubjectBiochemical Research Methods ; Mathematical & Computational Biology
WOS IDWOS:000456736200009
PublisherOXFORD UNIV PRESS
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Cited Times:1[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Identifierhttp://ir.amss.ac.cn/handle/2S8OKBNM/32349
Collection应用数学研究所
Affiliation1.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
Recommended Citation
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.
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