{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,8]],"date-time":"2026-06-08T19:41:36Z","timestamp":1780947696097,"version":"3.54.1"},"reference-count":60,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2018,6,19]],"date-time":"2018-06-19T00:00:00Z","timestamp":1529366400000},"content-version":"tdm","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":["61772381"],"award-info":[{"award-number":["61772381"]}],"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":["61572368"],"award-info":[{"award-number":["61572368"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Fundamental Research Funds for the Central Universities","award":["2042017kf0219"],"award-info":[{"award-number":["2042017kf0219"]}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["BMC Bioinformatics"],"published-print":{"date-parts":[[2018,12]]},"DOI":"10.1186\/s12859-018-2220-4","type":"journal-article","created":{"date-parts":[[2018,6,19]],"date-time":"2018-06-19T01:23:27Z","timestamp":1529371407000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":277,"title":["Predicting drug-disease associations by using similarity constrained matrix factorization"],"prefix":"10.1186","volume":"19","author":[{"given":"Wen","family":"Zhang","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xiang","family":"Yue","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Weiran","family":"Lin","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Wenjian","family":"Wu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ruoqi","family":"Liu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Feng","family":"Huang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Feng","family":"Liu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2018,6,19]]},"reference":[{"issue":"10","key":"2220_CR1","doi-asserted-by":"publisher","first-page":"793","DOI":"10.7326\/0003-4819-145-10-200611210-00024","volume":"145","author":"JF Wilson","year":"2006","unstructured":"Wilson JF. Alterations in processes and priorities needed for new drug development. Ann Intern Med. 2006;145(10):793\u20136.","journal-title":"Ann Intern Med"},{"issue":"5","key":"2220_CR2","doi-asserted-by":"publisher","first-page":"286","DOI":"10.1067\/mcp.2001.115132","volume":"69","author":"JA Dimasi","year":"2001","unstructured":"Dimasi JA. New drug development in the United States from 1963 to 1999. Clin Pharmacol Ther. 2001;69(5):286\u201396.","journal-title":"Clin Pharmacol Ther"},{"issue":"2","key":"2220_CR3","doi-asserted-by":"publisher","first-page":"420","DOI":"10.1377\/hlthaff.25.2.420","volume":"25","author":"CP Adams","year":"2006","unstructured":"Adams CP, Brantner VV. Estimating the cost of new drug development: is it really 802 million dollars? Health Aff. 2006;25(2):420\u20138.","journal-title":"Health Aff"},{"issue":"D1","key":"2220_CR4","doi-asserted-by":"publisher","first-page":"D972","DOI":"10.1093\/nar\/gkw838","volume":"45","author":"AP Davis","year":"2017","unstructured":"Davis AP, Grondin CJ, Johnson RJ, Sciaky D, King BL, McMorran R, Wiegers J, Wiegers TC, Mattingly CJ. The comparative Toxicogenomics database: update 2017. Nucleic Acids Res. 2017;45(D1):D972\u20138.","journal-title":"Nucleic Acids Res"},{"issue":"Database","key":"2220_CR5","doi-asserted-by":"publisher","first-page":"D1060","DOI":"10.1093\/nar\/gkq1037","volume":"39","author":"J von Eichborn","year":"2011","unstructured":"von Eichborn J, Murgueitio MS, Dunkel M, Koerner S, Bourne PE, Preissner R. PROMISCUOUS: a database for network-based drug-repositioning. Nucleic Acids Res. 2011;39(Database):D1060\u20136.","journal-title":"Nucleic Acids Res"},{"key":"2220_CR6","first-page":"e146","volume":"3","author":"L Wang","year":"2014","unstructured":"Wang L, Wang Y, Hu Q, Li S. Systematic analysis of new drug indications by drug-gene-disease coherent subnetworks. CPT: pharmacometrics & systems pharmacology. 2014;3:e146.","journal-title":"CPT: pharmacometrics & systems pharmacology"},{"key":"2220_CR7","doi-asserted-by":"publisher","first-page":"326","DOI":"10.1186\/1471-2105-10-326","volume":"10","author":"TC Wiegers","year":"2009","unstructured":"Wiegers TC, Davis AP, Cohen KB, Hirschman L, Mattingly CJ. Text mining and manual curation of chemical-gene-disease networks for the comparative toxicogenomics database (CTD). BMC Bioinformatics. 2009;10:326.","journal-title":"BMC Bioinformatics"},{"key":"2220_CR8","doi-asserted-by":"crossref","unstructured":"Yu L, Huang J, Ma Z, Zhang J, Zou Y, Gao L. Inferring drug-disease associations based on known protein complexes. BMC Med Genet. 2015;8(Suppl 2, S2)","DOI":"10.1186\/1755-8794-8-S2-S2"},{"key":"2220_CR9","doi-asserted-by":"publisher","first-page":"496","DOI":"10.1038\/msb.2011.26","volume":"7","author":"A Gottlieb","year":"2011","unstructured":"Gottlieb A, Stein GY, Ruppin E, Sharan R. PREDICT: a method for inferring novel drug indications with application to personalized medicine. Mol Syst Biol. 2011;7:496.","journal-title":"Mol Syst Biol"},{"issue":"12","key":"2220_CR10","doi-asserted-by":"publisher","first-page":"e28025","DOI":"10.1371\/journal.pone.0028025","volume":"6","author":"L Yang","year":"2011","unstructured":"Yang L, Agarwal P. Systematic drug repositioning based on clinical side-effects. PLoS One. 2011;6(12):e28025.","journal-title":"PLoS One"},{"issue":"11","key":"2220_CR11","doi-asserted-by":"publisher","first-page":"e78518","DOI":"10.1371\/journal.pone.0078518","volume":"8","author":"Y Wang","year":"2013","unstructured":"Wang Y, Chen S, Deng N, Wang Y. Drug repositioning by kernel-based integration of molecular structure, molecular activity, and phenotype data. PLoS One. 2013;8(11):e78518.","journal-title":"PLoS One"},{"issue":"Suppl 3","key":"2220_CR12","first-page":"S4","volume":"6","author":"YF Huang","year":"2013","unstructured":"Huang YF, Yeh HY, Soo VW. Inferring drug-disease associations from integration of chemical, genomic and phenotype data using network propagation. BMC Med Genet. 2013;6(Suppl 3):S4.","journal-title":"BMC Med Genet"},{"issue":"10","key":"2220_CR13","doi-asserted-by":"publisher","first-page":"e111668","DOI":"10.1371\/journal.pone.0111668","volume":"9","author":"M Oh","year":"2014","unstructured":"Oh M, Ahn J, Yoon Y. A network-based classification model for deriving novel drug-disease associations and assessing their molecular actions. PLoS One. 2014;9(10):e111668.","journal-title":"PLoS One"},{"issue":"20","key":"2220_CR14","doi-asserted-by":"publisher","first-page":"2923","DOI":"10.1093\/bioinformatics\/btu403","volume":"30","author":"W Wang","year":"2014","unstructured":"Wang W, Yang S, Zhang X, Li J. Drug repositioning by integrating target information through a heterogeneous network model. Bioinformatics. 2014;30(20):2923\u201330.","journal-title":"Bioinformatics"},{"issue":"1","key":"2220_CR15","doi-asserted-by":"publisher","first-page":"41","DOI":"10.1016\/j.artmed.2014.11.003","volume":"63","author":"V Martinez","year":"2015","unstructured":"Martinez V, Navarro C, Cano C, Fajardo W, Blanco A. DrugNet: network-based drug-disease prioritization by integrating heterogeneous data. Artif Intell Med. 2015;63(1):41\u20139.","journal-title":"Artif Intell Med"},{"issue":"5","key":"2220_CR16","doi-asserted-by":"publisher","first-page":"451","DOI":"10.1002\/cpt.82","volume":"97","author":"H Wang","year":"2015","unstructured":"Wang H, Gu Q, Wei J, Cao Z, Liu Q. Mining drug-disease relationships as a complement to medical genetics-based drug repositioning: where a recommendation system meets genome-wide association studies. Clin Pharmacol Ther. 2015;97(5):451\u20134.","journal-title":"Clin Pharmacol Ther"},{"issue":"8","key":"2220_CR17","doi-asserted-by":"publisher","first-page":"609","DOI":"10.1080\/1062936X.2016.1209241","volume":"27","author":"H Moghadam","year":"2016","unstructured":"Moghadam H, Rahgozar M, Gharaghani S. Scoring multiple features to predict drug disease associations using information fusion and aggregation. SAR QSAR Environ Res. 2016;27(8):609\u201328.","journal-title":"SAR QSAR Environ Res"},{"issue":"8","key":"2220_CR18","doi-asserted-by":"crossref","first-page":"1187","DOI":"10.1093\/bioinformatics\/btw770","volume":"33","author":"X Liang","year":"2017","unstructured":"Liang X, Zhang P, Yan L, Fu Y, Peng F, Qu L, Shao M, Chen Y, Chen Z. LRSSL: predict and interpret drug\u2013disease associations based on data integration using sparse subspace learning. Bioinformatics. 2017;33(8):1187\u201396.","journal-title":"Bioinformatics"},{"issue":"23\u201324","key":"2220_CR19","doi-asserted-by":"publisher","first-page":"1052","DOI":"10.1016\/j.drudis.2010.10.003","volume":"15","author":"Q Li","year":"2010","unstructured":"Li Q, Cheng T, Wang Y, Bryant SH. PubChem as a public resource for drug discovery. Drug Discov Today. 2010;15(23\u201324):1052\u20137.","journal-title":"Drug Discov Today"},{"issue":"Database issue","key":"2220_CR20","doi-asserted-by":"publisher","first-page":"D1091","DOI":"10.1093\/nar\/gkt1068","volume":"42","author":"V Law","year":"2014","unstructured":"Law V, Knox C, Djoumbou Y, Jewison T, Guo AC, Liu Y, Maciejewski A, Arndt D, Wilson M, Neveu V, et al. DrugBank 4.0: shedding new light on drug metabolism. Nucleic Acids Res. 2014;42(Database issue):D1091\u20137.","journal-title":"Nucleic Acids Res"},{"issue":"Database issue","key":"2220_CR21","doi-asserted-by":"publisher","first-page":"D355","DOI":"10.1093\/nar\/gkp896","volume":"38","author":"M Kanehisa","year":"2010","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. 2010;38(Database issue):D355\u201360.","journal-title":"Nucleic Acids Res"},{"issue":"2","key":"2220_CR22","doi-asserted-by":"publisher","first-page":"645","DOI":"10.1093\/nar\/13.2.645","volume":"13","author":"TF Smith","year":"1985","unstructured":"Smith TF, Waterman MS, Burks C. The statistical distribution of nucleic acid similarities. Nucleic Acids Res. 1985;13(2):645\u201356.","journal-title":"Nucleic Acids Res"},{"issue":"2","key":"2220_CR23","doi-asserted-by":"publisher","first-page":"133","DOI":"10.1089\/cmb.2010.0213","volume":"18","author":"L Perlman","year":"2011","unstructured":"Perlman L, Gottlieb A, Atias N, Ruppin E, Sharan R. Combining drug and gene similarity measures for drug-target elucidation. J Comput Biol. 2011;18(2):133\u201345.","journal-title":"J Comput Biol"},{"issue":"1","key":"2220_CR24","doi-asserted-by":"publisher","first-page":"11","DOI":"10.1186\/1756-0381-1-11","volume":"1","author":"K Ovaska","year":"2008","unstructured":"Ovaska K, Laakso M, Hautaniemi S. Fast gene ontology based clustering for microarray experiments. BioData Min. 2008;1(1):11.","journal-title":"BioData Min"},{"key":"2220_CR25","doi-asserted-by":"publisher","first-page":"15","DOI":"10.1016\/j.jbi.2014.03.014","volume":"51","author":"F Wang","year":"2014","unstructured":"Wang F, Zhang P, Cao N, Hu J, Sorrentino R. Exploring the associations between drug side-effects and therapeutic indications. J Biomed Inform. 2014;51:15\u201323.","journal-title":"J Biomed Inform"},{"issue":"8","key":"2220_CR26","doi-asserted-by":"publisher","first-page":"e70204","DOI":"10.1371\/journal.pone.0070204","volume":"8","author":"P Xuan","year":"2013","unstructured":"Xuan P, Han K, Guo M, Guo Y, Li J, Ding J, Liu Y, Dai Q, Li J, Teng Z, et al. Prediction of microRNAs associated with human diseases based on weighted k most similar neighbors. PLoS One. 2013;8(8):e70204.","journal-title":"PLoS One"},{"key":"2220_CR27","doi-asserted-by":"publisher","first-page":"11338","DOI":"10.1038\/srep11338","volume":"5","author":"X Chen","year":"2015","unstructured":"Chen X, Yan CC, Luo C, Ji W, Zhang Y, Dai Q. Constructing lncRNA functional similarity network based on lncRNA-disease associations and disease semantic similarity. Sci Rep. 2015;5:11338.","journal-title":"Sci Rep"},{"issue":"13","key":"2220_CR28","doi-asserted-by":"publisher","first-page":"1644","DOI":"10.1093\/bioinformatics\/btq241","volume":"26","author":"D Wang","year":"2010","unstructured":"Wang D, Wang J, Lu M, Song F, Cui Q. Inferring the human microRNA functional similarity and functional network based on microRNA-associated diseases. Bioinformatics. 2010;26(13):1644\u201350.","journal-title":"Bioinformatics"},{"key":"2220_CR29","volume-title":"Manifold learning theory and applications","author":"Y Ma","year":"2012","unstructured":"Ma Y, Fu Y. Manifold learning theory and applications. Boca Raton: CRC; Taylor & Francis distributor; 2012."},{"key":"2220_CR30","doi-asserted-by":"publisher","first-page":"154","DOI":"10.1016\/j.neucom.2018.01.085","volume":"287","author":"W Zhang","year":"2018","unstructured":"Zhang W, Liu X, Chen Y, Wu W, Wang W, Li X. Feature-derived graph regularized matrix factorization for predicting drug side effects. Neurocomputing. 2018;287:154\u201362.","journal-title":"Neurocomputing"},{"issue":"3","key":"2220_CR31","doi-asserted-by":"publisher","first-page":"245","DOI":"10.1002\/ima.22141","volume":"25","author":"B Rana","year":"2015","unstructured":"Rana B, Juneja A, Saxena M, Gudwani S, Kumaran SS, Behari M, Agrawal RK. Graph-theory-based spectral feature selection for computer aided diagnosis of Parkinson's disease using T1-weighted MRI International Journal of Imaging Systems and Technology Volume 25, Issue 3. Int J Imaging Syst Technol. 2015;25(3):245\u201355.","journal-title":"Int J Imaging Syst Technol"},{"key":"2220_CR32","unstructured":"Chung FRK: Spectral graph theory. Providence, R.I.: published for the conference board of the mathematical sciences by the American Mathematical Society; 1997."},{"issue":"12","key":"2220_CR33","doi-asserted-by":"publisher","first-page":"2056","DOI":"10.3390\/molecules22122056","volume":"22","author":"W Zhang","year":"2017","unstructured":"Zhang W, Chen Y, Li D. Drug-target interaction prediction through label propagation with linear neighborhood information. Molecules. 2017;22(12):2056.","journal-title":"Molecules"},{"key":"2220_CR34","doi-asserted-by":"publisher","first-page":"526","DOI":"10.1016\/j.neucom.2017.07.065","volume":"273","author":"W Zhang","year":"2018","unstructured":"Zhang W, Qu Q, Zhang Y, Wang W. The linear neighborhood propagation method for predicting long non-coding RNA\u2013protein interactions. Neurocomputing. 2018;273:526\u201334.","journal-title":"Neurocomputing"},{"key":"2220_CR35","doi-asserted-by":"crossref","unstructured":"Zhang W, Yue X, Chen Y, Lin W, Li B, Liu F, Li X. Predicting drug-disease associations based on the known association bipartite network. IEEE Int Conf Bioinformatics Biomed. 2017:503\u20139.","DOI":"10.1109\/BIBM.2017.8217698"},{"key":"2220_CR36","doi-asserted-by":"crossref","unstructured":"Zhang W, Chen Y, Tu S, Liu F, Qu Q. Drug side effect prediction through linear neighborhoods and multiple data source integration. IEEE Int C Bioinform. 2016:427\u201334.","DOI":"10.1109\/BIBM.2016.7822555"},{"key":"2220_CR37","first-page":"417","volume":"2017","author":"CY Ruan","year":"2017","unstructured":"Ruan CY, Wang Y, Zhang YC, Ma JG, Chen HJ, Aickelin U, Zhu SF, Zhang T. THCluster:herb supplements categorization for precision traditional Chinese medicine. IEEE Int Conf Bioinformatics And Biomedicine. 2017;2017:417\u201324.","journal-title":"IEEE Int Conf Bioinformatics And Biomedicine"},{"key":"2220_CR38","doi-asserted-by":"crossref","unstructured":"Zhang W, Yue X, Liu F, Chen YL, Tu SK, Zhang XN. A unified frame of predicting side effects of drugs by using linear neighborhood similarity. BMC Syst Biol. 2017;11","DOI":"10.1186\/s12918-017-0477-2"},{"issue":"3","key":"2220_CR39","doi-asserted-by":"publisher","first-page":"162","DOI":"10.1056\/NEJM199307153290303","volume":"329","author":"JM Alvir","year":"1993","unstructured":"Alvir JM, Lieberman JA, Safferman AZ, Schwimmer JL, Schaaf JA. Clozapine-induced agranulocytosis. Incidence and risk factors in the United States. N Engl J Med. 1993;329(3):162\u20137.","journal-title":"N Engl J Med"},{"issue":"Suppl 1","key":"2220_CR40","doi-asserted-by":"publisher","first-page":"1","DOI":"10.2165\/00002018-199200071-00003","volume":"7","author":"JA Lieberman","year":"1992","unstructured":"Lieberman JA, Alvir JM. A report of clozapine-induced agranulocytosis in the United States. Incidence and risk factors. Drug Saf. 1992;7(Suppl 1):1\u20132.","journal-title":"Drug Saf"},{"issue":"10","key":"2220_CR41","doi-asserted-by":"publisher","first-page":"469","DOI":"10.1111\/pcn.12435","volume":"70","author":"M Fujimoto","year":"2016","unstructured":"Fujimoto M, Hashimoto R, Yamamori H, Yasuda Y, Ohi K, Iwatani H, Isaka Y, Takeda M. Clozapine improved the syndrome of inappropriate antidiuretic hormone secretion in a patient with treatment-resistant schizophrenia. Psychiatry Clin Neurosci. 2016;70(10):469.","journal-title":"Psychiatry Clin Neurosci"},{"key":"2220_CR42","unstructured":"Abejuela HR, Festin FE, Lynn E. Clozapine for Treatment- Resistant Post-Traumatic Stress Disorder (PTSD). J Traum Stress Disord Treatment. 2014;3(2):1\u20139."},{"issue":"1","key":"2220_CR43","doi-asserted-by":"publisher","first-page":"57","DOI":"10.1089\/104454604773840490","volume":"14","author":"R Kant","year":"2004","unstructured":"Kant R, Chalansani R, Chengappa KN, Dieringer MF. The off-label use of clozapine in adolescents with bipolar disorder, intermittent explosive disorder, or posttraumatic stress disorder. J Child Adolesc Psychopharmacol. 2004;14(1):57.","journal-title":"J Child Adolesc Psychopharmacol"},{"issue":"1","key":"2220_CR44","doi-asserted-by":"publisher","first-page":"8","DOI":"10.1097\/00002826-200301000-00003","volume":"26","author":"C Klein","year":"2003","unstructured":"Klein C, Gordon J, Pollak L, Rabey JM. Clozapine in Parkinson's disease psychosis: 5-year follow-up review. Clin Neuropharmacol. 2003;26(1):8\u201311.","journal-title":"Clin Neuropharmacol"},{"issue":"4","key":"2220_CR45","doi-asserted-by":"publisher","first-page":"557","DOI":"10.1016\/j.pbb.2011.06.011","volume":"99","author":"O Mutlu","year":"2011","unstructured":"Mutlu O, Ulak G, Celikyurt IK, Akar FY, Erden F, Tanyeri P. Effects of olanzapine, sertindole and clozapine on MK-801 induced visual memory deficits in mice. Pharmacol Biochem Behav. 2011;99(4):557\u201365.","journal-title":"Pharmacol Biochem Behav"},{"issue":"9","key":"2220_CR46","doi-asserted-by":"publisher","first-page":"1321","DOI":"10.1345\/aph.1D050","volume":"37","author":"RA Schatz","year":"2003","unstructured":"Schatz RA. Olanzapine for psychotic and behavioral disturbances in Alzheimer disease. Ann Pharmacother. 2003;37(9):1321\u20134.","journal-title":"Ann Pharmacother"},{"issue":"8","key":"2220_CR47","doi-asserted-by":"publisher","first-page":"1192","DOI":"10.1016\/j.neurobiolaging.2007.11.010","volume":"30","author":"O Ambr\u00e9e","year":"2009","unstructured":"Ambr\u00e9e O, Richter H, Sachser N, Lewejohann L, Dere E, Ma DSS, Herring A, Keyvani K, Paulus W, Sch\u00e4bitz WR. Levodopa ameliorates learning and memory deficits in a murine model of Alzheimer's disease. Neurobiol Aging. 2009;30(8):1192\u2013204.","journal-title":"Neurobiol Aging"},{"issue":"2016\u20131-22","key":"2220_CR48","first-page":"4","volume":"4","author":"N L\u00f3pezriquelme","year":"2016","unstructured":"L\u00f3pezriquelme N, Alompoveda J, Vicianomorote N, Llinaresibor I, Tormod\u00edaz C. Apolipoprotein E \u03b54 allele and malondialdehyde level are independent risk factors for Alzheimer\u2019s disease. SAGE Open Med. 2016;4(2016\u20131-22):4.","journal-title":"SAGE Open Med"},{"issue":"48","key":"2220_CR49","doi-asserted-by":"publisher","first-page":"13357","DOI":"10.1523\/JNEUROSCI.2718-07.2007","volume":"27","author":"JC Carroll","year":"2007","unstructured":"Carroll JC, Rosario ER, Chang L, Stanczyk FZ, Oddo S, Laferla FM, Pike CJ. Progesterone and estrogen regulate Alzheimer-like neuropathology in female 3xTg-AD mice. J. Neurosci. Off. J. Soc. Neurosci. 2007;27(48):13357.","journal-title":"J. Neurosci. Off. J. Soc. Neurosci"},{"issue":"12","key":"2220_CR50","doi-asserted-by":"publisher","first-page":"2781","DOI":"10.1084\/jem.20081588","volume":"205","author":"Q Hong","year":"2008","unstructured":"Hong Q, He G, Ly PTT, Fox CJ, Staufenbiel M, Cai F, Zhang Z, Wei S, Sun X, Chen CH. Valproic acid inhibits A\u03b2 production, neuritic plaque formation, and behavioral deficits in Alzheimer's disease mouse models. J Exp Med. 2008;205(12):2781.","journal-title":"J Exp Med"},{"issue":"8","key":"2220_CR51","doi-asserted-by":"publisher","first-page":"1406","DOI":"10.1016\/j.neuropharm.2011.08.030","volume":"61","author":"C Bate","year":"2011","unstructured":"Bate C, Williams A. Ethanol protects cultured neurons against amyloid-\u03b2 and \u03b1-synuclein-induced synapse damage. Neuropharmacology. 2011;61(8):1406\u201312.","journal-title":"Neuropharmacology"},{"key":"2220_CR52","doi-asserted-by":"publisher","first-page":"150","DOI":"10.1016\/j.jbi.2017.03.003","volume":"68","author":"T Cohen","year":"2017","unstructured":"Cohen T, Widdows D. Embedding of semantic predications. J Biomed Inform. 2017;68:150\u201366.","journal-title":"J Biomed Inform"},{"key":"2220_CR53","first-page":"1940","volume":"2016","author":"J Mower","year":"2016","unstructured":"Mower J, Subramanian D, Shang N, Cohen T. Classification-by-analogy: using vector representations of implicit relationships to identify plausibly causal drug\/side-effect relationships. AMIA Annu Symp Proc. 2016;2016:1940\u20139.","journal-title":"AMIA Annu Symp Proc"},{"issue":"Suppl 13","key":"2220_CR54","doi-asserted-by":"publisher","first-page":"464","DOI":"10.1186\/s12859-017-1875-6","volume":"18","author":"W Zhang","year":"2017","unstructured":"Zhang W, Zhu X, Fu Y, Tsuji J, Weng Z. Predicting human splicing branchpoints by combining sequence-derived features and multi-label learning methods. BMC Bioinformatics. 2017;18(Suppl 13):464.","journal-title":"BMC Bioinformatics"},{"issue":"5","key":"2220_CR55","doi-asserted-by":"publisher","first-page":"e0128194","DOI":"10.1371\/journal.pone.0128194","volume":"10","author":"W Zhang","year":"2015","unstructured":"Zhang W, Niu Y, Zou H, Luo L, Liu Q, Wu W. Accurate prediction of immunogenic T-cell epitopes from epitope sequences using the genetic algorithm-based ensemble learning. PLoS One. 2015;10(5):e0128194.","journal-title":"PLoS One"},{"key":"2220_CR56","doi-asserted-by":"publisher","first-page":"365","DOI":"10.1186\/s12859-015-0774-y","volume":"16","author":"W Zhang","year":"2015","unstructured":"Zhang W, Liu F, Luo L, Zhang J. Predicting drug side effects by multi-label learning and ensemble learning. BMC Bioinformatics. 2015;16:365.","journal-title":"BMC Bioinformatics"},{"issue":"1","key":"2220_CR57","doi-asserted-by":"publisher","first-page":"329","DOI":"10.1186\/s12859-016-1206-3","volume":"17","author":"D Li","year":"2016","unstructured":"Li D, Luo L, Zhang W, Liu F, Luo F. A genetic algorithm-based weighted ensemble method for predicting transposon-derived piRNAs. BMC Bioinformatics. 2016;17(1):329.","journal-title":"BMC Bioinformatics"},{"key":"2220_CR58","doi-asserted-by":"crossref","unstructured":"Luo L, Li D, Zhang W, Tu S, Zhu X, Tian G. Accurate prediction of transposon-derived piRNAs by integrating various sequential and physicochemical features. PLoS One. 2016;11(4).","DOI":"10.1371\/journal.pone.0153268"},{"key":"2220_CR59","doi-asserted-by":"crossref","unstructured":"Zhang W, Chen YL, Liu F, Luo F, Tian G, Li XH. Predicting potential drug-drug interactions by integrating chemical, biological, phenotypic and network data. Bmc Bioinformatics. 2017;18:18.","DOI":"10.1186\/s12859-016-1415-9"},{"key":"2220_CR60","first-page":"643","volume":"2017","author":"W Zhang","year":"2017","unstructured":"Zhang W, Shi JW, Tang GF, Wu WJ, Yue X, Li DF. Predicting small RNAs in bacteria via sequence learning ensemble method. IEEE Int Conf Bioinformatics Biomed. 2017;2017:643\u20137.","journal-title":"IEEE Int Conf Bioinformatics Biomed"}],"container-title":["BMC Bioinformatics"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1186\/s12859-018-2220-4.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/article\/10.1186\/s12859-018-2220-4\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1186\/s12859-018-2220-4.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,9,3]],"date-time":"2023-09-03T07:11:05Z","timestamp":1693725065000},"score":1,"resource":{"primary":{"URL":"https:\/\/bmcbioinformatics.biomedcentral.com\/articles\/10.1186\/s12859-018-2220-4"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2018,6,19]]},"references-count":60,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2018,12]]}},"alternative-id":["2220"],"URL":"https:\/\/doi.org\/10.1186\/s12859-018-2220-4","relation":{},"ISSN":["1471-2105"],"issn-type":[{"value":"1471-2105","type":"electronic"}],"subject":[],"published":{"date-parts":[[2018,6,19]]},"assertion":[{"value":"11 October 2017","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"28 May 2018","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"19 June 2018","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":"The authors declare that they have no competing interests.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Competing interests"}},{"value":"Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Publisher\u2019s Note"}}],"article-number":"233"}}