{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,9,26]],"date-time":"2025-09-26T22:08:59Z","timestamp":1758924539513},"reference-count":56,"publisher":"Springer Science and Business Media LLC","issue":"S1","content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["BMC Med Inform Decis Mak"],"published-print":{"date-parts":[[2017,5]]},"DOI":"10.1186\/s12911-017-0450-4","type":"journal-article","created":{"date-parts":[[2017,5,18]],"date-time":"2017-05-18T07:48:53Z","timestamp":1495093733000},"update-policy":"http:\/\/dx.doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":5,"title":["An inference method from multi-layered structure of biomedical data"],"prefix":"10.1186","volume":"17","author":[{"given":"Myungjun","family":"Kim","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yonghyun","family":"Nam","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hyunjung","family":"Shin","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2017,5,18]]},"reference":[{"key":"450_CR1","doi-asserted-by":"crossref","unstructured":"Ishii N, Tomita M. Multi-omics data-driven systems biology of E. coli. In: Systems biology and biotechnology of Escherichia coli. Springer Netherlands; 2009. p. 41\u201357.","DOI":"10.1007\/978-1-4020-9394-4_3"},{"issue":"2","key":"450_CR2","doi-asserted-by":"crossref","first-page":"85","DOI":"10.1038\/nrg3868","volume":"16","author":"MD Ritchie","year":"2015","unstructured":"Ritchie MD, Holzinger ER, Li R, Pendergrass SA, Kim D. Methods of integrating data to uncover genotype-phenotype interactions. Nat Rev Genet. 2015;16(2):85\u201397.","journal-title":"Nat Rev Genet"},{"issue":"2","key":"450_CR3","first-page":"167","volume":"17","author":"M Bersanelli","year":"2016","unstructured":"Bersanelli M, Mosca E, Remondini D, Giampieri E, Sala C, Castellani G, Milanesi L. Methods for the integration of multi-omics data: mathematical aspects. BMC bioinformatics. 2016;17(2):167.","journal-title":"BMC bioinformatics"},{"issue":"5","key":"450_CR4","doi-asserted-by":"crossref","first-page":"333","DOI":"10.1038\/nrg3433","volume":"14","author":"B Berger","year":"2013","unstructured":"Berger B, Peng J, Singh M. Computational solutions for omics data. Nat Rev Genet. 2013;14(5):333\u201346.","journal-title":"Nat Rev Genet"},{"key":"450_CR5","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.ymeth.2015.06.003","volume":"83","author":"S Kim","year":"2015","unstructured":"Kim S. Network based approaches to the analysis of omics data. Methods (San Diego, Calif). 2015;83:1\u20132.","journal-title":"Methods (San Diego, Calif)"},{"issue":"1","key":"450_CR6","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1186\/1752-0509-2-95","volume":"2","author":"AP Presson","year":"2008","unstructured":"Presson AP, Sobel EM, Papp JC, Suarez CJ, Whistler T, Rajeevan MS, Vernon SD, Horvath S. Integrated weighted gene co-expression network analysis with an application to chronic fatigue syndrome. BMC Syst Biol. 2008;2(1):1.","journal-title":"BMC Syst Biol"},{"issue":"5643","key":"450_CR7","doi-asserted-by":"crossref","first-page":"249","DOI":"10.1126\/science.1087447","volume":"302","author":"JM Stuart","year":"2003","unstructured":"Stuart JM, Segal E, Koller D, Kim SK. A gene-coexpression network for global discovery of conserved genetic modules. Science. 2003;302(5643):249\u201355.","journal-title":"Science"},{"key":"450_CR8","doi-asserted-by":"crossref","unstructured":"Weirauch MT. Gene coexpression networks for the analysis of DNA microarray data. Appl Stat Netw Biol. 2011:215\u2013250.","DOI":"10.1002\/9783527638079.ch11"},{"key":"450_CR9","unstructured":"Butte AJ, Kohane IS. Mutual information relevance networks: functional genomic clustering using pairwise entropy measurements. In: Pacific Symposium on Biocomputing. 2000;5:418-429."},{"key":"450_CR10","doi-asserted-by":"crossref","first-page":"281","DOI":"10.1016\/S0076-6879(10)70012-4","volume":"470","author":"M Dreze","year":"2010","unstructured":"Dreze M, Monachello D, Lurin C, Cusick ME, Hill DE, Vidal M, Braun P. High-quality binary interactome mapping. Methods Enzymol. 2010;470:281\u2013315.","journal-title":"Methods Enzymol"},{"issue":"7062","key":"450_CR11","doi-asserted-by":"crossref","first-page":"1173","DOI":"10.1038\/nature04209","volume":"437","author":"J-F Rual","year":"2005","unstructured":"Rual J-F, Venkatesan K, Hao T, Hirozane-Kishikawa T, Dricot A, Li N, Berriz GF, Gibbons FD, Dreze M, Ayivi-Guedehoussou N. Towards a proteome-scale map of the human protein\u2013protein interaction network. Nature. 2005;437(7062):1173\u20138.","journal-title":"Nature"},{"issue":"1","key":"450_CR12","doi-asserted-by":"crossref","first-page":"83","DOI":"10.1038\/nmeth.1280","volume":"6","author":"K Venkatesan","year":"2009","unstructured":"Venkatesan K, Rual J-F, Vazquez A, Stelzl U, Lemmens I, Hirozane-Kishikawa T, Hao T, Zenkner M, Xin X, Goh K-I. An empirical framework for binary interactome mapping. Nat Methods. 2009;6(1):83\u201390.","journal-title":"Nat Methods"},{"issue":"6","key":"450_CR13","doi-asserted-by":"crossref","first-page":"957","DOI":"10.1016\/j.cell.2005.08.029","volume":"122","author":"U Stelzl","year":"2005","unstructured":"Stelzl U, Worm U, Lalowski M, Haenig C, Brembeck FH, Goehler H, Stroedicke M, Zenkner M, Schoenherr A, Koeppen S. A human protein-protein interaction network: a resource for annotating the proteome. Cell. 2005;122(6):957\u201368.","journal-title":"Cell"},{"issue":"6","key":"450_CR14","doi-asserted-by":"crossref","first-page":"1777","DOI":"10.1073\/pnas.0610772104","volume":"104","author":"NC Duarte","year":"2007","unstructured":"Duarte NC, Becker SA, Jamshidi N, Thiele I, Mo ML, Vo TD, Srivas R, Palsson B\u00d8. Global reconstruction of the human metabolic network based on genomic and bibliomic data. Proc Natl Acad Sci. 2007;104(6):1777\u201382.","journal-title":"Proc Natl Acad Sci"},{"issue":"1","key":"450_CR15","doi-asserted-by":"crossref","first-page":"135","DOI":"10.1038\/msb4100177","volume":"3","author":"H Ma","year":"2007","unstructured":"Ma H, Sorokin A, Mazein A, Selkov A, Selkov E, Demin O, Goryanin I. The Edinburgh human metabolic network reconstruction and its functional analysis. Mol Syst Biol. 2007;3(1):135.","journal-title":"Mol Syst Biol"},{"issue":"21","key":"450_CR16","doi-asserted-by":"crossref","first-page":"8685","DOI":"10.1073\/pnas.0701361104","volume":"104","author":"K-I Goh","year":"2007","unstructured":"Goh K-I, Cusick ME, Valle D, Childs B, Vidal M, Barab\u00e1si A-L. The human disease network. Proc Natl Acad Sci. 2007;104(21):8685\u201390.","journal-title":"Proc Natl Acad Sci"},{"key":"450_CR17","doi-asserted-by":"crossref","unstructured":"Zhou X, Menche J, Barab\u00e1si A-L, Sharma A. Human symptoms\u2013disease network. Nat Commun. 2014;5.","DOI":"10.1038\/ncomms5212"},{"issue":"4","key":"450_CR18","doi-asserted-by":"crossref","first-page":"276","DOI":"10.1016\/j.tibtech.2015.12.013","volume":"34","author":"K Yugi","year":"2016","unstructured":"Yugi K, Kubota H, Hatano A, Kuroda S. Trans-Omics: How To Reconstruct Biochemical Networks Across Multiple \u2018Omic\u2019Layers. Trends Biotechnol. 2016;34(4):276\u201390.","journal-title":"Trends Biotechnol"},{"issue":"5","key":"450_CR19","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1186\/1752-0509-9-S5-S1","volume":"9","author":"A Stanescu","year":"2015","unstructured":"Stanescu A, Caragea D. An empirical study of ensemble-based semi-supervised learning approaches for imbalanced splice site datasets. BMC Syst Biol. 2015;9(5):1.","journal-title":"BMC Syst Biol"},{"key":"450_CR20","doi-asserted-by":"crossref","unstructured":"Belkin M, Matveeva I, Niyogi P. Regularization and semi-supervised learning on large graphs. In: International Conference on Computational Learning Theory: 2004. Springer. p. 624\u2013638.","DOI":"10.1109\/ICASSP.2004.1326716"},{"issue":"Nov","key":"450_CR21","first-page":"2399","volume":"7","author":"M Belkin","year":"2006","unstructured":"Belkin M, Niyogi P, Sindhwani V. Manifold regularization: A geometric framework for learning from labeled and unlabeled examples. J Mach Learn Res. 2006;7(Nov):2399\u2013434.","journal-title":"J Mach Learn Res"},{"issue":"16","key":"450_CR22","first-page":"321","volume":"16","author":"D Zhou","year":"2004","unstructured":"Zhou D, Bousquet O, Lal TN, Weston J, Sch\u00f6lkopf B. Learning with local and global consistency. Adv Neural Inf Proces Syst. 2004;16(16):321\u20138.","journal-title":"Adv Neural Inf Proces Syst"},{"key":"450_CR23","unstructured":"Zhu X, Ghahramani Z, Lafferty J. Semi-supervised learning using gaussian fields and harmonic functions. In: Proceedings of the Twenty-first International Conference on Machine Learning (ICML). 2003;3:912\u2013919."},{"key":"450_CR24","unstructured":"Chapelle O, Weston J, Sch\u00f6lkopf B. Cluster kernels for semi-supervised learning. In: Proceedings of the Advances in Neural Information Processing Systems 15 (NIPS). 2002;585\u2013592."},{"key":"450_CR25","unstructured":"Zhu X, Ghahramani Z. Learning from labeled and unlabeled data with label propagation. In: Citeseer; 2002"},{"key":"450_CR26","doi-asserted-by":"crossref","unstructured":"Chung FR. Spectral graph theory. Issue 92 in Regional Conference Series in Mathematics. Providence RI. American Mathematical Soc. 1997.","DOI":"10.1090\/cbms\/092"},{"issue":"2","key":"450_CR27","doi-asserted-by":"crossref","first-page":"3284","DOI":"10.1016\/j.eswa.2008.01.006","volume":"36","author":"H Shin","year":"2009","unstructured":"Shin H, Tsuda K, Sch\u00f6lkopf B. Protein functional class prediction with a combined graph. Expert Syst Appl. 2009;36(2):3284\u201392.","journal-title":"Expert Syst Appl"},{"key":"450_CR28","first-page":"361","volume-title":"Prediction of protein function from networks","author":"H Shin","year":"2006","unstructured":"Shin H, Tsuda K, Sch\u00f6lkopf B, Zien A. Prediction of protein function from networks. In: Semi-supervised learning. MIT press; 2006. p. 361\u201376."},{"issue":"suppl 2","key":"450_CR29","doi-asserted-by":"crossref","first-page":"ii59","DOI":"10.1093\/bioinformatics\/bti1110","volume":"21","author":"K Tsuda","year":"2005","unstructured":"Tsuda K, Shin H, Sch\u00f6lkopf B. Fast protein classification with multiple networks. Bioinformatics. 2005;21 suppl 2:ii59\u201365.","journal-title":"Bioinformatics"},{"issue":"23","key":"450_CR30","doi-asserted-by":"crossref","first-page":"3217","DOI":"10.1093\/bioinformatics\/btm511","volume":"23","author":"H Shin","year":"2007","unstructured":"Shin H, Lisewski AM, Lichtarge O. Graph sharpening plus graph integration: a synergy that improves protein functional classification. Bioinformatics. 2007;23(23):3217\u201324.","journal-title":"Bioinformatics"},{"issue":"6","key":"450_CR31","doi-asserted-by":"crossref","first-page":"1191","DOI":"10.1016\/j.jbi.2012.07.008","volume":"45","author":"D Kim","year":"2012","unstructured":"Kim D, Shin H, Song YS, Kim JH. Synergistic effect of different levels of genomic data for cancer clinical outcome prediction. J Biomed Inform. 2012;45(6):1191\u20138.","journal-title":"J Biomed Inform"},{"issue":"1","key":"450_CR32","doi-asserted-by":"crossref","first-page":"109","DOI":"10.1136\/amiajnl-2013-002481","volume":"22","author":"D Kim","year":"2015","unstructured":"Kim D, Joung J-G, Sohn K-A, Shin H, Park YR, Ritchie MD, Kim JH. Knowledge boosting: a graph-based integration approach with multi-omics data and genomic knowledge for cancer clinical outcome prediction. J Am Med Inform Assoc. 2015;22(1):109\u201320.","journal-title":"J Am Med Inform Assoc"},{"issue":"3","key":"450_CR33","doi-asserted-by":"crossref","first-page":"344","DOI":"10.1016\/j.ymeth.2014.02.003","volume":"67","author":"D Kim","year":"2014","unstructured":"Kim D, Shin H, Sohn K-A, Verma A, Ritchie MD, Kim JH. Incorporating inter-relationships between different levels of genomic data into cancer clinical outcome prediction. Methods. 2014;67(3):344\u201353.","journal-title":"Methods"},{"issue":"1","key":"450_CR34","doi-asserted-by":"crossref","first-page":"63","DOI":"10.1016\/j.artmed.2011.09.003","volume":"54","author":"T-P Nguyen","year":"2012","unstructured":"Nguyen T-P, Ho T-B. Detecting disease genes based on semi-supervised learning and protein\u2013protein interaction networks. Artif Intell Med. 2012;54(1):63\u201371.","journal-title":"Artif Intell Med"},{"issue":"1","key":"450_CR35","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1186\/1471-2105-11-1","volume":"11","author":"Z-H You","year":"2010","unstructured":"You Z-H, Yin Z, Han K, Huang D-S, Zhou X. A semi-supervised learning approach to predict synthetic genetic interactions by combining functional and topological properties of functional gene network. Bmc Bioinformatics. 2010;11(1):1.","journal-title":"Bmc Bioinformatics"},{"issue":"3","key":"450_CR36","first-page":"1","volume":"7","author":"D Kim","year":"2013","unstructured":"Kim D, Shin H, Joung J-G, Lee S-Y, Kim JH. Intra-relation reconstruction from inter-relation: miRNA to gene expression. BMC Syst Biol. 2013;7(3):1.","journal-title":"BMC Syst Biol"},{"key":"450_CR37","doi-asserted-by":"crossref","unstructured":"Chen X, Yan G-Y. Semi-supervised learning for potential human microRNA-disease associations inference. Sci Rep. 2014;4:5501.","DOI":"10.1038\/srep05501"},{"issue":"3","key":"450_CR38","doi-asserted-by":"crossref","first-page":"72","DOI":"10.1186\/s12911-016-0315-2","volume":"16","author":"Y Nam","year":"2016","unstructured":"Nam Y, Kim M, Lee K, Shin H. CLASH: Complementary Linkage with Anchoring and Scoring for Heterogeneous biomolecular and clinical data. BMC Med Inform Decis Mak. 2016;16(3):72.","journal-title":"BMC Med Inform Decis Mak"},{"key":"450_CR39","unstructured":"Williams C, Seeger M. Using the Nystr\u00f6m method to speed up kernel machines. In: Proceedings of the 14th annual conference on neural information processing systems: 2001. p. 682\u2013688."},{"key":"450_CR40","first-page":"106","volume":"42","author":"MA Woodbury","year":"1950","unstructured":"Woodbury MA. Inverting modified matrices. Memorandum Rep. 1950;42:106.","journal-title":"Memorandum Rep"},{"key":"450_CR41","doi-asserted-by":"crossref","unstructured":"Bengio Y, Delalleau O, Le Roux N. Label propagation and quadratic criterion. Semi-supervised Learn. 2006;10.","DOI":"10.7551\/mitpress\/6173.003.0016"},{"issue":"1","key":"450_CR42","doi-asserted-by":"crossref","first-page":"015001","DOI":"10.1088\/1749-4680\/8\/1\/015001","volume":"8","author":"NM Boffi","year":"2014","unstructured":"Boffi NM, Hill JC, Reuter MG. Characterizing the inverses of block tridiagonal, block Toeplitz matrices. Comput Sci Discov. 2014;8(1):015001.","journal-title":"Comput Sci Discov"},{"issue":"2","key":"450_CR43","doi-asserted-by":"crossref","first-page":"221","DOI":"10.1137\/1031049","volume":"31","author":"WW Hager","year":"1989","unstructured":"Hager WW. Updating the inverse of a matrix. SIAM Rev. 1989;31(2):221\u201339.","journal-title":"SIAM Rev"},{"issue":"3","key":"450_CR44","doi-asserted-by":"crossref","first-page":"707","DOI":"10.1137\/0613045","volume":"13","author":"G Meurant","year":"1992","unstructured":"Meurant G. A review on the inverse of symmetric tridiagonal and block tridiagonal matrices. SIAM J Matrix Anal Appl. 1992;13(3):707\u201328.","journal-title":"SIAM J Matrix Anal Appl"},{"issue":"6","key":"450_CR45","doi-asserted-by":"crossref","first-page":"245","DOI":"10.1016\/j.parco.2013.03.003","volume":"39","author":"AV Terekhov","year":"2013","unstructured":"Terekhov AV. A fast parallel algorithm for solving block-tridiagonal systems of linear equations including the domain decomposition method. Parallel Comput. 2013;39(6):245\u201358.","journal-title":"Parallel Comput"},{"key":"450_CR46","doi-asserted-by":"crossref","unstructured":"Degenhardt L, Hall W, Lynskey M. What is comorbidity and why does it occur? Comorbid Mental disorders and substance use disorders: Epidemiology, prevention and treatment. 2003;10\u201325.","DOI":"10.1037\/e677042010-003"},{"issue":"20","key":"450_CR47","doi-asserted-by":"crossref","first-page":"2441","DOI":"10.1001\/jama.291.20.2441","volume":"291","author":"JF Piccirillo","year":"2004","unstructured":"Piccirillo JF, Tierney RM, Costas I, Grove L, Spitznagel Jr EL. Prognostic importance of comorbidity in a hospital-based cancer registry. Jama. 2004;291(20):2441\u20137.","journal-title":"Jama"},{"issue":"4","key":"450_CR48","doi-asserted-by":"crossref","first-page":"593","DOI":"10.1097\/00005537-200004000-00011","volume":"110","author":"JF Piccirillo","year":"2000","unstructured":"Piccirillo JF. Importance of comorbidity in head and neck cancer. Laryngoscope. 2000;110(4):593\u2013602.","journal-title":"Laryngoscope"},{"key":"450_CR49","unstructured":"U.S. National Library of Medicine, Medical Subject Headings ( www.ncbi.nlm.nih.gov\/mesh , Acessed 5 Jan 2016)"},{"key":"450_CR50","unstructured":"HuDiNe ( www.hudine.neu.edu , Acessed 17 Jan 2016)"},{"key":"450_CR51","unstructured":"Tanimoto TT. elementary mathematical theory of classification and prediction. New York; 1958."},{"key":"450_CR52","doi-asserted-by":"crossref","unstructured":"Swets JA. Signal detection theory and ROC analysis in psychology and diagnostics: Collected papers. New York. Psychology Press; 2014.","DOI":"10.4324\/9781315806167"},{"issue":"4","key":"450_CR53","doi-asserted-by":"crossref","first-page":"421","DOI":"10.1109\/34.19039","volume":"11","author":"K Fukunaga","year":"1989","unstructured":"Fukunaga K, Hummels DM. Leave-one-out procedures for nonparametric error estimates. IEEE Trans Pattern Anal Mach Intell. 1989;11(4):421\u20133.","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"issue":"37","key":"450_CR54","doi-asserted-by":"crossref","first-page":"149","DOI":"10.1016\/j.mpmed.2008.12.007","volume":"3","author":"V McDonald","year":"2009","unstructured":"McDonald V, Scully M. Causes of thrombocytopenia. Medicine. 2009;3(37):149\u201354.","journal-title":"Medicine"},{"issue":"20","key":"450_CR55","doi-asserted-by":"crossref","first-page":"1330","DOI":"10.1056\/NEJM199505183322003","volume":"332","author":"TE Warkentin","year":"1995","unstructured":"Warkentin TE, Levine MN, Hirsh J, Horsewood P, Roberts RS, Gent M, Kelton JG. Heparin-induced thrombocytopenia in patients treated with low-molecular-weight heparin or unfractionated heparin. N Engl J Med. 1995;332(20):1330\u20136.","journal-title":"N Engl J Med"},{"issue":"1","key":"450_CR56","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1186\/1471-2105-15-S6-S1","volume":"15","author":"K Sun","year":"2014","unstructured":"Sun K, Gon\u00e7alves JP, Larminie C, Pr\u017eulj N. Predicting disease associations via biological network analysis. BMC bioinformatics. 2014;15(1):1.","journal-title":"BMC bioinformatics"}],"container-title":["BMC Medical Informatics and Decision Making"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1186\/s12911-017-0450-4.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,8,23]],"date-time":"2023-08-23T16:39:07Z","timestamp":1692808747000},"score":1,"resource":{"primary":{"URL":"http:\/\/bmcmedinformdecismak.biomedcentral.com\/articles\/10.1186\/s12911-017-0450-4"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2017,5]]},"references-count":56,"journal-issue":{"issue":"S1","published-print":{"date-parts":[[2017,5]]}},"alternative-id":["450"],"URL":"https:\/\/doi.org\/10.1186\/s12911-017-0450-4","relation":{},"ISSN":["1472-6947"],"issn-type":[{"value":"1472-6947","type":"electronic"}],"subject":[],"published":{"date-parts":[[2017,5]]},"article-number":"52"}}