{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,27]],"date-time":"2026-02-27T04:10:57Z","timestamp":1772165457627,"version":"3.50.1"},"reference-count":47,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2020,10,30]],"date-time":"2020-10-30T00:00:00Z","timestamp":1604016000000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"},{"start":{"date-parts":[[2020,10,30]],"date-time":"2020-10-30T00:00:00Z","timestamp":1604016000000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["11401017"],"award-info":[{"award-number":["11401017"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["11671025"],"award-info":[{"award-number":["11671025"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["11290141"],"award-info":[{"award-number":["11290141"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Artificial Intelligence Project","award":["2018AAA0102301"],"award-info":[{"award-number":["2018AAA0102301"]}]},{"name":"Fundamental Research of Civil Aircraft","award":["MJ-F-2012-04"],"award-info":[{"award-number":["MJ-F-2012-04"]}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["BMC Bioinformatics"],"published-print":{"date-parts":[[2020,12]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>Classification of diseases based on genetic information is of great significance as the basis for precision medicine, increasing the understanding of disease etiology and revolutionizing personalized medicine. Much effort has been directed at understanding disease associations by constructing disease networks, and classifying patient samples according to gene expression data. Integrating human gene networks overcomes limited coverage of genes. Incorporating pathway information into disease classification procedure addresses the challenge of cellular heterogeneity across patients.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>In this work, we propose a disease classification model LAMP, which concentrates on the layered assessment on modules and pathways. Directed human gene interactions are the foundation of constructing the human gene network, where the significant roles of disease and pathway genes are recognized. The fast unfolding algorithm identifies 11 modules in the largest connected component. Then layered networks are introduced to distinguish positions of genes in propagating information from sources to targets. After gene screening, hierarchical clustering and refined process, 1726 diseases from KEGG are classified into 18 categories. Also, it is expounded that diseases with overlapping genes may not belong to the same category in LAMP. Within each category, entropy is applied to measure the compositional complexity, and to evaluate the prospects for combination diagnosis and gene-targeted therapy for diseases.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>In this work, by collecting data from BioGRID and KEGG, we develop a disease classification model LAMP, to support people to view diseases from the perspective of commonalities in etiology and pathology. Comprehensive research on existing diseases can help meet the challenges of unknown diseases. The results provide suggestions for combination diagnosis and gene-targeted therapy, which motivates clinicians and researchers to reposition the understanding of diseases and explore diagnosis and therapy strategies.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1186\/s12859-020-03800-2","type":"journal-article","created":{"date-parts":[[2020,10,30]],"date-time":"2020-10-30T05:06:43Z","timestamp":1604034403000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["LAMP: disease classification derived from layered assessment on modules and pathways in the human gene network"],"prefix":"10.1186","volume":"21","author":[{"given":"Zhilong","family":"Mi","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0540-3779","authenticated-orcid":false,"given":"Binghui","family":"Guo","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xiaobo","family":"Yang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ziqiao","family":"Yin","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zhiming","family":"Zheng","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2020,10,30]]},"reference":[{"issue":"1","key":"3800_CR1","doi-asserted-by":"publisher","first-page":"124","DOI":"10.1038\/msb4100163","volume":"3","author":"J Loscalzo","year":"2007","unstructured":"Loscalzo J, Kohane I, Barabasi A-L. Human disease classification in the postgenomic era: a complex systems approach to human pathobiology. Mol Syst Biol. 2007;3(1):124.","journal-title":"Mol Syst Biol"},{"issue":"2","key":"3800_CR2","doi-asserted-by":"publisher","first-page":"4346","DOI":"10.1371\/journal.pone.0004346","volume":"4","author":"Y Li","year":"2009","unstructured":"Li Y, Agarwal P. A pathway-based view of human diseases and disease relationships. PLoS ONE. 2009;4(2):4346.","journal-title":"PLoS ONE"},{"issue":"7","key":"3800_CR3","doi-asserted-by":"publisher","first-page":"190214","DOI":"10.1098\/rsos.190214","volume":"6","author":"Z Mi","year":"2019","unstructured":"Mi Z, Guo B, Yin Z, Li J, Zheng Z. Disease classification via gene network integrating modules and pathways. R Soc Open Sci. 2019;6(7):190214.","journal-title":"R Soc Open Sci"},{"issue":"11","key":"3800_CR4","doi-asserted-by":"publisher","first-page":"1000217","DOI":"10.1371\/journal.pcbi.1000217","volume":"4","author":"E Lee","year":"2008","unstructured":"Lee E, Chuang H-Y, Kim J-W, Ideker T, Lee D. Inferring pathway activity toward precise disease classification. PLoS Comput Biol. 2008;4(11):1000217.","journal-title":"PLoS Comput Biol"},{"issue":"12","key":"3800_CR5","doi-asserted-by":"publisher","first-page":"8161","DOI":"10.1371\/journal.pone.0008161","volume":"4","author":"J Su","year":"2009","unstructured":"Su J, Yoon B-J, Dougherty ER. Accurate and reliable cancer classification based on probabilistic inference of pathway activity. PLoS ONE. 2009;4(12):8161.","journal-title":"PLoS ONE"},{"issue":"5","key":"3800_CR6","doi-asserted-by":"publisher","first-page":"1769","DOI":"10.1093\/bib\/bby049","volume":"20","author":"MG Dozmorov","year":"2019","unstructured":"Dozmorov MG. Disease classification: from phenotypic similarity to integrative genomics and beyond. Brief Bioinform. 2019;20(5):1769\u201380.","journal-title":"Brief Bioinform"},{"issue":"3","key":"3800_CR7","doi-asserted-by":"publisher","first-page":"359","DOI":"10.1161\/CIRCRESAHA.111.258541","volume":"111","author":"SY Chan","year":"2012","unstructured":"Chan SY, Loscalzo J. The emerging paradigm of network medicine in the study of human disease. Circ Res. 2012;111(3):359\u201374.","journal-title":"Circ Res"},{"issue":"1","key":"3800_CR8","doi-asserted-by":"publisher","first-page":"54","DOI":"10.7150\/jca.10631","volume":"6","author":"J Wang","year":"2015","unstructured":"Wang J, Zuo Y, Man Y-G, Avital I, Stojadinovic A, Liu M, Yang X, Varghese RS, Tadesse MG, Ressom HW. Pathway and network approaches for identification of cancer signature markers from omics data. J Cancer. 2015;6(1):54.","journal-title":"J Cancer"},{"key":"3800_CR9","doi-asserted-by":"publisher","first-page":"294","DOI":"10.3389\/fgene.2019.00294","volume":"10","author":"AR Sonawane","year":"2019","unstructured":"Sonawane AR, Weiss ST, Glass K, Sharma A. Network medicine in the age of biomedical big data. Front Genet. 2019;10:294.","journal-title":"Front Genet"},{"issue":"1","key":"3800_CR10","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1186\/s13039-019-0468-7","volume":"12","author":"MA Zelenova","year":"2019","unstructured":"Zelenova MA, Yurov YB, Vorsanova SG, Iourov IY. Laundering CNV data for candidate process prioritization in brain disorders. Mol Cytogenet. 2019;12(1):1\u20136.","journal-title":"Mol Cytogenet"},{"issue":"1","key":"3800_CR11","doi-asserted-by":"publisher","first-page":"27","DOI":"10.1093\/nar\/28.1.27","volume":"28","author":"M Kanehisa","year":"2000","unstructured":"Kanehisa M, Goto S. Kegg: kyoto encyclopedia of genes and genomes. Nucleic Acids Res. 2000;28(1):27\u201330.","journal-title":"Nucleic Acids Res"},{"issue":"suppl-1","key":"3800_CR12","first-page":"355","volume":"38","author":"M Kanehisa","year":"2009","unstructured":"Kanehisa M, Goto S, Furumichi M, Tanabe M, Hirakawa M. Kegg for representation and analysis of molecular networks involving diseases and drugs. Nucleic Acids Res. 2009;38(suppl-1):355\u201360.","journal-title":"Nucleic Acids Res"},{"issue":"suppl-1","key":"3800_CR13","doi-asserted-by":"publisher","first-page":"61","DOI":"10.1093\/nar\/gkl842","volume":"35","author":"KD Pruitt","year":"2007","unstructured":"Pruitt KD, Tatusova T, Maglott DR. Ncbi reference sequences (refseq): a curated non-redundant sequence database of genomes, transcripts and proteins. Nucleic Acids Res. 2007;35(suppl-1):61\u20135.","journal-title":"Nucleic Acids Res"},{"issue":"1","key":"3800_CR14","doi-asserted-by":"publisher","first-page":"56","DOI":"10.1038\/nrg2918","volume":"12","author":"A-L Barab\u00e1si","year":"2011","unstructured":"Barab\u00e1si A-L, Gulbahce N, Loscalzo J. Network medicine: a network-based approach to human disease. Nat Rev Genet. 2011;12(1):56\u201368.","journal-title":"Nat Rev Genet"},{"issue":"10","key":"3800_CR15","doi-asserted-by":"publisher","first-page":"10008","DOI":"10.1088\/1742-5468\/2008\/10\/P10008","volume":"2008","author":"VD Blondel","year":"2008","unstructured":"Blondel VD, Guillaume J-L, Lambiotte R, Lefebvre E. Fast unfolding of communities in large networks. J Stat Mech Theory Exp. 2008;2008(10):10008.","journal-title":"J Stat Mech Theory Exp"},{"issue":"4","key":"3800_CR16","doi-asserted-by":"publisher","first-page":"225","DOI":"10.1137\/0202019","volume":"2","author":"JE Hopcroft","year":"1973","unstructured":"Hopcroft JE, Karp RM. An n^5\/2 algorithm for maximum matchings in bipartite graphs. SIAM J Comput. 1973;2(4):225\u201331.","journal-title":"SIAM J Comput"},{"issue":"7346","key":"3800_CR17","doi-asserted-by":"publisher","first-page":"167","DOI":"10.1038\/nature10011","volume":"473","author":"Y-Y Liu","year":"2011","unstructured":"Liu Y-Y, Slotine J-J, Barab\u00e1si A-L. Controllability of complex networks. Nature. 2011;473(7346):167\u201373.","journal-title":"Nature"},{"issue":"3","key":"3800_CR18","doi-asserted-by":"publisher","first-page":"263","DOI":"10.1007\/BF01318865","volume":"15","author":"G Fisher","year":"1998","unstructured":"Fisher G, Lorenzo N, Abe H, Fujita E, Frey W, Emory C, Di Fiore MM, D\u2019Aniello A. Free d-and l-amino acids in ventricular cerebrospinal fluid from alzheimer and normal subjects. Amino Acids. 1998;15(3):263\u20139.","journal-title":"Amino Acids"},{"issue":"1","key":"3800_CR19","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1038\/s41598-016-0028-x","volume":"7","author":"C-H Lin","year":"2017","unstructured":"Lin C-H, Yang H-T, Chiu C-C, Lane H-Y. Blood levels of d-amino acid oxidase vs. d-amino acids in reflecting cognitive aging. Sci Rep. 2017;7(1):1\u201310.","journal-title":"Sci Rep"},{"issue":"2","key":"3800_CR20","doi-asserted-by":"publisher","first-page":"179","DOI":"10.1016\/j.psychres.2007.02.007","volume":"153","author":"S Chung","year":"2007","unstructured":"Chung S, Hong JP, Yoo HK. Association of the DAO and DAOA gene polymorphisms with autism spectrum disorders in boys in Korea: a preliminary study. Psychiatry Res. 2007;153(2):179\u201382.","journal-title":"Psychiatry Res"},{"issue":"21","key":"3800_CR21","doi-asserted-by":"publisher","first-page":"13675","DOI":"10.1073\/pnas.182412499","volume":"99","author":"I Chumakov","year":"2002","unstructured":"Chumakov I, Blumenfeld M, Guerassimenko O, Cavarec L, Palicio M, Abderrahim H, Bougueleret L, Barry C, Tanaka H, La Rosa P, et al. Genetic and physiological data implicating the new human gene g72 and the gene for d-amino acid oxidase in schizophrenia. Proc Natl Acad Sci. 2002;99(21):13675\u201380.","journal-title":"Proc Natl Acad Sci"},{"issue":"9","key":"3800_CR22","doi-asserted-by":"publisher","first-page":"678","DOI":"10.1016\/j.biopsych.2013.08.010","volume":"75","author":"C-H Lin","year":"2014","unstructured":"Lin C-H, Chen P-K, Chang Y-C, Chuo L-J, Chen Y-S, Tsai GE, Lane H-Y. Benzoate, a d-amino acid oxidase inhibitor, for the treatment of early-phase alzheimer disease: a randomized, double-blind, placebo-controlled trial. Biol Psychiatry. 2014;75(9):678\u201385.","journal-title":"Biol Psychiatry"},{"issue":"1","key":"3800_CR23","doi-asserted-by":"publisher","first-page":"192","DOI":"10.4172\/2161-1025.1000192","volume":"7","author":"P Yang","year":"2017","unstructured":"Yang P, Lane H, Hsu H, Chang C. A pilot trial of sodium benzoate, a d-amino acid oxidase inhibitor, added on augmentative and alternative communication intervention for non-communicative children with autism spectrum disorders. Transl Med (Sunnyvale). 2017;7(1):192.","journal-title":"Transl Med (Sunnyvale)"},{"issue":"6","key":"3800_CR24","doi-asserted-by":"publisher","first-page":"422","DOI":"10.1016\/j.biopsych.2017.12.006","volume":"84","author":"C-H Lin","year":"2018","unstructured":"Lin C-H, Lin C-H, Chang Y-C, Huang Y-J, Chen P-W, Yang H-T, Lane H-Y. Sodium benzoate, a d-amino acid oxidase inhibitor, added to clozapine for the treatment of schizophrenia: a randomized, double-blind, placebo-controlled trial. Biol Psychiatry. 2018;84(6):422\u201332.","journal-title":"Biol Psychiatry"},{"issue":"10","key":"3800_CR25","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1038\/nmicrobiol.2016.125","volume":"1","author":"J Sasabe","year":"2016","unstructured":"Sasabe J, Miyoshi Y, Rakoff-Nahoum S, Zhang T, Mita M, Davis BM, Hamase K, Waldor MK. Interplay between microbial d-amino acids and host d-amino acid oxidase modifies murine mucosal defence and gut microbiota. Nat Microbiol. 2016;1(10):1\u20137.","journal-title":"Nat Microbiol"},{"key":"3800_CR26","doi-asserted-by":"publisher","first-page":"21","DOI":"10.1146\/annurev-neuro-072116-031347","volume":"40","author":"HE Vuong","year":"2017","unstructured":"Vuong HE, Yano JM, Fung TC, Hsiao EY. The microbiome and host behavior. Annu Rev Neurosci. 2017;40:21\u201349.","journal-title":"Annu Rev Neurosci"},{"issue":"Nov","key":"3800_CR27","first-page":"2579","volume":"9","author":"LVD van der Maaten","year":"2008","unstructured":"van der Maaten LVD, Hinton G. Visualizing data using t-SNE. J Mach Learn Res. 2008;9(Nov):2579\u2013605.","journal-title":"J Mach Learn Res"},{"issue":"1","key":"3800_CR28","first-page":"3221","volume":"15","author":"L Van Der Maaten","year":"2014","unstructured":"Van Der Maaten L. Accelerating t-SNE using tree-based algorithms. J Mach Learn Res. 2014;15(1):3221\u201345.","journal-title":"J Mach Learn Res"},{"issue":"10","key":"3800_CR29","doi-asserted-by":"publisher","first-page":"2","DOI":"10.23915\/distill.00002","volume":"1","author":"M Wattenberg","year":"2016","unstructured":"Wattenberg M, Vi\u00e9gas F, Johnson I. How to use t-SNE effectively. Distill. 2016;1(10):2.","journal-title":"Distill"},{"key":"3800_CR30","first-page":"2825","volume":"12","author":"F Pedregosa","year":"2011","unstructured":"Pedregosa F, Varoquaux G, Gramfort A, Michel V, Thirion B, Grisel O, Blondel M, Prettenhofer P, Weiss R, Dubourg V, Vanderplas J, Passos A, Cournapeau D, Brucher M, Perrot M, Duchesnay E. Scikit-learn: machine learning in Python. J Mach Learn Res. 2011;12:2825\u201330.","journal-title":"J Mach Learn Res"},{"issue":"10","key":"3800_CR31","doi-asserted-by":"publisher","first-page":"615","DOI":"10.1038\/nrg.2016.87","volume":"17","author":"JX Hu","year":"2016","unstructured":"Hu JX, Thomas CE, Brunak S. Network biology concepts in complex disease comorbidities. Nat Rev Genet. 2016;17(10):615.","journal-title":"Nat Rev Genet"},{"issue":"7","key":"3800_CR32","doi-asserted-by":"publisher","first-page":"2031","DOI":"10.1053\/j.gastro.2006.04.008","volume":"130","author":"RK Patel","year":"2006","unstructured":"Patel RK, Lea NC, Heneghan MA, Westwood NB, Milojkovic D, Thanigaikumar M, Yallop D, Arya R, Pagliuca A, G\u00e4ken J, et al. Prevalence of the activating jak2 tyrosine kinase mutation v617f in the budd-chiari syndrome. Gastroenterology. 2006;130(7):2031\u20138.","journal-title":"Gastroenterology"},{"issue":"5","key":"3800_CR33","doi-asserted-by":"publisher","first-page":"822","DOI":"10.1016\/j.cell.2009.08.017","volume":"138","author":"M Shackleton","year":"2009","unstructured":"Shackleton M, Quintana E, Fearon ER, Morrison SJ. Heterogeneity in cancer: cancer stem cells versus clonal evolution. Cell. 2009;138(5):822\u20139.","journal-title":"Cell"},{"issue":"7467","key":"3800_CR34","doi-asserted-by":"publisher","first-page":"338","DOI":"10.1038\/nature12625","volume":"501","author":"RA Burrell","year":"2013","unstructured":"Burrell RA, McGranahan N, Bartek J, Swanton C. The causes and consequences of genetic heterogeneity in cancer evolution. Nature. 2013;501(7467):338\u201345.","journal-title":"Nature"},{"issue":"7457","key":"3800_CR35","doi-asserted-by":"publisher","first-page":"214","DOI":"10.1038\/nature12213","volume":"499","author":"MS Lawrence","year":"2013","unstructured":"Lawrence MS, Stojanov P, Polak P, Kryukov GV, Cibulskis K, Sivachenko A, Carter SL, Stewart C, Mermel CH, Roberts SA, et al. Mutational heterogeneity in cancer and the search for new cancer-associated genes. Nature. 2013;499(7457):214\u20138.","journal-title":"Nature"},{"issue":"7467","key":"3800_CR36","doi-asserted-by":"publisher","first-page":"328","DOI":"10.1038\/nature12624","volume":"501","author":"CE Meacham","year":"2013","unstructured":"Meacham CE, Morrison SJ. Tumour heterogeneity and cancer cell plasticity. Nature. 2013;501(7467):328\u201337.","journal-title":"Nature"},{"issue":"9","key":"3800_CR37","doi-asserted-by":"publisher","first-page":"149","DOI":"10.1007\/s11306-016-1094-6","volume":"12","author":"RD Beger","year":"2016","unstructured":"Beger RD, Dunn W, Schmidt MA, Gross SS, Kirwan JA, Cascante M, Brennan L, Wishart DS, Oresic M, Hankemeier T, et al. Metabolomics enables precision medicine: \u201ca white paper, community perspective\u201d. Metabolomics. 2016;12(9):149.","journal-title":"Metabolomics"},{"issue":"6822","key":"3800_CR38","doi-asserted-by":"publisher","first-page":"853","DOI":"10.1038\/35057050","volume":"409","author":"G Jimenez-Sanchez","year":"2001","unstructured":"Jimenez-Sanchez G, Childs B, Valle D. Human disease genes. Nature. 2001;409(6822):853\u20135.","journal-title":"Nature"},{"issue":"1","key":"3800_CR39","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1146\/annurev.genom.1.1.1","volume":"1","author":"B Childs","year":"2000","unstructured":"Childs B, Valle D. Genetics, biology and disease. Annu Rev Genomics Hum Genet. 2000;1(1):1\u201319.","journal-title":"Annu Rev Genomics Hum Genet"},{"issue":"21","key":"3800_CR40","doi-asserted-by":"publisher","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"},{"issue":"1","key":"3800_CR41","doi-asserted-by":"publisher","first-page":"13","DOI":"10.1007\/s00125-015-3789-z","volume":"59","author":"RD Leslie","year":"2016","unstructured":"Leslie RD, Palmer J, Schloot NC, Lernmark A. Diabetes at the crossroads: relevance of disease classification to pathophysiology and treatment. Diabetologia. 2016;59(1):13\u201320.","journal-title":"Diabetologia"},{"issue":"4","key":"3800_CR42","doi-asserted-by":"publisher","first-page":"286","DOI":"10.1038\/nrd2826","volume":"8","author":"EE Schadt","year":"2009","unstructured":"Schadt EE, Friend SH, Shaywitz DA. A network view of disease and compound screening. Nat Rev Drug Discov. 2009;8(4):286\u201395.","journal-title":"Nat Rev Drug Discov"},{"issue":"2","key":"3800_CR43","doi-asserted-by":"publisher","first-page":"446","DOI":"10.1021\/ci500670q","volume":"55","author":"H Iwata","year":"2015","unstructured":"Iwata H, Sawada R, Mizutani S, Yamanishi Y. Systematic drug repositioning for a wide range of diseases with integrative analyses of phenotypic and molecular data. J Chem Inf Model. 2015;55(2):446\u201359.","journal-title":"J Chem Inf Model"},{"issue":"3","key":"3800_CR44","doi-asserted-by":"publisher","first-page":"229","DOI":"10.1111\/joim.12412","volume":"279","author":"M Benson","year":"2016","unstructured":"Benson M. Clinical implications of omics and systems medicine: focus on predictive and individualized treatment. J Intern Med. 2016;279(3):229\u201340.","journal-title":"J Intern Med"},{"key":"3800_CR45","doi-asserted-by":"publisher","first-page":"214","DOI":"10.1016\/j.jclinepi.2015.09.016","volume":"70","author":"JM Gaziano","year":"2016","unstructured":"Gaziano JM, Concato J, Brophy M, Fiore L, Pyarajan S, Breeling J, Whitbourne S, Deen J, Shannon C, Humphries D, et al. Million veteran program: a mega-biobank to study genetic influences on health and disease. J Clin Epidemiol. 2016;70:214\u201323.","journal-title":"J Clin Epidemiol"},{"issue":"suppl-1","key":"3800_CR46","doi-asserted-by":"publisher","first-page":"535","DOI":"10.1093\/nar\/gkj109","volume":"34","author":"C Stark","year":"2006","unstructured":"Stark C, Breitkreutz B-J, Reguly T, Boucher L, Breitkreutz A, Tyers M. Biogrid: a general repository for interaction datasets. Nucleic Acids Res. 2006;34(suppl-1):535\u20139.","journal-title":"Nucleic Acids Res"},{"issue":"3","key":"3800_CR47","doi-asserted-by":"publisher","first-page":"274","DOI":"10.1007\/s00357-014-9161-z","volume":"31","author":"F Murtagh","year":"2014","unstructured":"Murtagh F, Legendre P. Ward\u2019s hierarchical agglomerative clustering method: which algorithms implement ward\u2019s criterion? J Classif. 2014;31(3):274\u201395.","journal-title":"J Classif"}],"container-title":["BMC Bioinformatics"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1186\/s12859-020-03800-2.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/article\/10.1186\/s12859-020-03800-2\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1186\/s12859-020-03800-2.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2020,11,1]],"date-time":"2020-11-01T20:02:59Z","timestamp":1604260979000},"score":1,"resource":{"primary":{"URL":"https:\/\/bmcbioinformatics.biomedcentral.com\/articles\/10.1186\/s12859-020-03800-2"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,10,30]]},"references-count":47,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2020,12]]}},"alternative-id":["3800"],"URL":"https:\/\/doi.org\/10.1186\/s12859-020-03800-2","relation":{"has-preprint":[{"id-type":"doi","id":"10.21203\/rs.3.rs-41665\/v3","asserted-by":"object"},{"id-type":"doi","id":"10.21203\/rs.3.rs-41665\/v1","asserted-by":"object"},{"id-type":"doi","id":"10.21203\/rs.3.rs-41665\/v2","asserted-by":"object"}]},"ISSN":["1471-2105"],"issn-type":[{"value":"1471-2105","type":"electronic"}],"subject":[],"published":{"date-parts":[[2020,10,30]]},"assertion":[{"value":"8 July 2020","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"5 October 2020","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"30 October 2020","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"Not applicable.","order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethics approval and consent to participate"}},{"value":"Not applicable.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Consent for publication"}},{"value":"The authors declare that they have no competing interests.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Competing interests"}}],"article-number":"487"}}