{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,23]],"date-time":"2025-10-23T11:15:22Z","timestamp":1761218122674},"reference-count":56,"publisher":"Springer Science and Business Media LLC","issue":"S9","license":[{"start":{"date-parts":[[2018,12,1]],"date-time":"2018-12-01T00:00:00Z","timestamp":1543622400000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["BMC Syst Biol"],"published-print":{"date-parts":[[2018,12]]},"DOI":"10.1186\/s12918-018-0658-7","type":"journal-article","created":{"date-parts":[[2018,12,31]],"date-time":"2018-12-31T08:36:34Z","timestamp":1546245394000},"update-policy":"http:\/\/dx.doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":14,"title":["Computational drug repositioning using meta-path-based semantic network analysis"],"prefix":"10.1186","volume":"12","author":[{"given":"Zhen","family":"Tian","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zhixia","family":"Teng","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Shuang","family":"Cheng","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Maozu","family":"Guo","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2018,12,31]]},"reference":[{"issue":"4","key":"658_CR1","first-page":"531","volume":"10","author":"L Yu","year":"2016","unstructured":"Yu L, Wang B, Ma X, Gao L. The extraction of drug-disease correlations based on module distance in incomplete human interactome. BMC Syst Biol. 2016;10(4):531.","journal-title":"BMC Syst Biol"},{"issue":"6","key":"658_CR2","doi-asserted-by":"publisher","first-page":"609","DOI":"10.1038\/clpt.1994.78","volume":"55","author":"JA DiMasi","year":"1994","unstructured":"DiMasi JA, Seibring MA, Lasagna L. New drug development in the United States from 1963 to 1992. Clin Pharmacol Ther. 1994;55(6):609\u201322.","journal-title":"Clin Pharmacol Ther"},{"key":"658_CR3","doi-asserted-by":"publisher","first-page":"10331","DOI":"10.1038\/ncomms10331","volume":"7","author":"E Guney","year":"2016","unstructured":"Guney E, Menche J, Vidal M, Bar\u00e1basi A-L. Network-based in silico drug efficacy screening. Nat Commun. 2016;7:10331.","journal-title":"Nat Commun"},{"issue":"3","key":"658_CR4","doi-asserted-by":"publisher","first-page":"203","DOI":"10.1038\/nrd3078","volume":"9","author":"SM Paul","year":"2010","unstructured":"Paul SM, Mytelka DS, Dunwiddie CT, Persinger CC, Munos BH, Lindborg SR, Schacht AL. How to improve R&D productivity: the pharmaceutical industry's grand challenge. Nat Rev Drug Discov. 2010;9(3):203\u201314.","journal-title":"Nat Rev Drug Discov"},{"issue":"1","key":"658_CR5","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(1):496.","journal-title":"Mol Syst Biol"},{"issue":"8","key":"658_CR6","doi-asserted-by":"publisher","first-page":"673","DOI":"10.1038\/nrd1468","volume":"3","author":"TT Ashburn","year":"2004","unstructured":"Ashburn TT, Thor KB. Drug repositioning: identifying and developing new uses for existing drugs. Nat Rev Drug Discov. 2004;3(8):673\u201383.","journal-title":"Nat Rev Drug Discov"},{"issue":"17","key":"658_CR7","doi-asserted-by":"publisher","first-page":"455","DOI":"10.1093\/bioinformatics\/btw433","volume":"32","author":"M Ammad-ud-din","year":"2016","unstructured":"Ammad-ud-din M, Khan SA, Malani D, Murumagi A, Kallioniemi O, Aittokallio T, Kaski S. Drug response prediction by inferring pathway-response associations with kernelized Bayesian matrix factorization. Bioinformatics. 2016;32(17):455\u201363.","journal-title":"Bioinformatics"},{"issue":"1","key":"658_CR8","doi-asserted-by":"publisher","first-page":"41","DOI":"10.1016\/j.artmed.2014.11.003","volume":"63","author":"V Mart\u00ednez","year":"2015","unstructured":"Mart\u00ednez V, Navarro C, Cano C, Fajardo W, Blanco A. DrugNet: network-based drug\u2013disease prioritization by integrating heterogeneous data. Artif Intell Med. 2015;63(1):41\u20139.","journal-title":"Artif Intell Med"},{"issue":"suppl 1","key":"658_CR9","doi-asserted-by":"publisher","first-page":"D1060","DOI":"10.1093\/nar\/gkq1037","volume":"39","author":"J Eichborn Von","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(suppl 1):D1060\u20136.","journal-title":"Nucleic Acids Res"},{"issue":"5","key":"658_CR10","doi-asserted-by":"publisher","first-page":"637","DOI":"10.1016\/j.drudis.2013.11.005","volume":"19","author":"G Jin","year":"2014","unstructured":"Jin G, Wong ST. Toward better drug repositioning: prioritizing and integrating existing methods into efficient pipelines. Drug Discov Today. 2014;19(5):637\u201344.","journal-title":"Drug Discov Today"},{"issue":"1","key":"658_CR11","doi-asserted-by":"publisher","first-page":"5","DOI":"10.2174\/1568026615666150112103510","volume":"15","author":"K Shameer","year":"2015","unstructured":"Shameer K, Readhead B, T Dudley J. Computational and experimental advances in drug repositioning for accelerated therapeutic stratification. Curr Top Med Chem. 2015;15(1):5\u201320.","journal-title":"Curr Top Med Chem"},{"issue":"20","key":"658_CR12","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":"658_CR13","doi-asserted-by":"publisher","first-page":"2","DOI":"10.1093\/bib\/bbv020","volume":"17","author":"J Li","year":"2016","unstructured":"Li J, Zheng S, Chen B, Butte AJ, Swamidass SJ, Lu Z. A survey of current trends in computational drug repositioning. Brief Bioinform. 2016;17(1):2\u201312.","journal-title":"Brief Bioinform"},{"key":"658_CR14","doi-asserted-by":"crossref","unstructured":"Maryam Lotfi Shahreza, Nasser Ghadiri, Sayed Rasoul Mousavi, Jaleh Varshosaz, James R Green; A review of network-based approaches to drug repositioning[J]. Briefings in Bioinformatics. 2018;19(5):878\u201392.","DOI":"10.1093\/bib\/bbx017"},{"issue":"2","key":"658_CR15","doi-asserted-by":"publisher","first-page":"408","DOI":"10.1021\/ci100369f","volume":"51","author":"SL Kinnings","year":"2011","unstructured":"Kinnings SL, Liu N, Tonge PJ, Jackson RM, Xie L, Bourne PE. A machine learning-based method to improve docking scoring functions and its application to drug repurposing. J Chem Inf Model. 2011;51(2):408\u201319.","journal-title":"J Chem Inf Model"},{"issue":"11","key":"658_CR16","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":"4","key":"658_CR17","doi-asserted-by":"publisher","first-page":"e61318","DOI":"10.1371\/journal.pone.0061318","volume":"8","author":"MP Menden","year":"2013","unstructured":"Menden MP, Iorio F, Garnett M, McDermott U, Benes CH, Ballester PJ, Saez-Rodriguez J. Machine learning prediction of cancer cell sensitivity to drugs based on genomic and chemical properties. PLoS One. 2013;8(4):e61318.","journal-title":"PLoS One"},{"issue":"1","key":"658_CR18","doi-asserted-by":"publisher","first-page":"30","DOI":"10.1186\/1758-2946-5-30","volume":"5","author":"F Napolitano","year":"2013","unstructured":"Napolitano F, Zhao Y, Moreira VM, Tagliaferri R, Kere J, D\u2019Amato M, Greco D. Drug repositioning: a machine-learning approach through data integration. J Cheminform. 2013;5(1):30.","journal-title":"J Cheminform"},{"key":"658_CR19","unstructured":"Zhang P, Wang F, Hu J. Towards drug repositioning: a unified computational framework for integrating multiple aspects of drug similarity and disease similarity. In: AMIA Annual Symposium Proceedings: American medical informatics association; 2014. p. 1258."},{"issue":"9","key":"658_CR20","doi-asserted-by":"publisher","first-page":"2562","DOI":"10.1021\/ci500340n","volume":"54","author":"J Yang","year":"2014","unstructured":"Yang J, Li Z, Fan X, Cheng Y. Drug\u2013disease association and drug-repositioning predictions in complex diseases using causal inference\u2013probabilistic matrix factorization. J Chem Inf Model. 2014;54(9):2562\u20139.","journal-title":"J Chem Inf Model"},{"key":"658_CR21","unstructured":"Wu G, Liu J, Wang C. Semi-supervised graph cut algorithm for drug repositioning by integrating drug, disease and genomic associations. In: Bioinformatics and Biomedicine (BIBM): IEEE International Conference on: 2016. IEEE; 2016. p. 223\u20138."},{"issue":"8","key":"658_CR22","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":"10","key":"658_CR23","doi-asserted-by":"publisher","first-page":"1119","DOI":"10.1038\/nbt1338","volume":"25","author":"MA Yildirim","year":"2007","unstructured":"Yildirim MA, Goh K-I, Cusick ME, Barabasi A-L, Vidal M. Drug--target network. Nat Biotechnol. 2007;25(10):1119.","journal-title":"Nat Biotechnol"},{"key":"658_CR24","doi-asserted-by":"crossref","unstructured":"Chandrasekaran SN, Huan J. Weighted multiview learning for predicting drug-disease associations. In: Bioinformatics and Biomedicine (BIBM): IEEE International Conference on: 2016. IEEE; 2016. p. 699\u2013702.","DOI":"10.1109\/BIBM.2016.7822603"},{"issue":"2","key":"658_CR25","doi-asserted-by":"publisher","first-page":"203","DOI":"10.2174\/1574893611666160125222144","volume":"11","author":"J Wang","year":"2016","unstructured":"Wang J, Kribelbauer J, Rabadan R. Network propagation reveals novel features predicting drug response of Cancer cell lines. Curr Bioinforma. 2016;11(2):203\u201310.","journal-title":"Curr Bioinforma"},{"issue":"7270","key":"658_CR26","doi-asserted-by":"publisher","first-page":"175","DOI":"10.1038\/nature08506","volume":"462","author":"MJ Keiser","year":"2009","unstructured":"Keiser MJ, Setola V, Irwin JJ, Laggner C, Abbas AI, Hufeisen SJ, Jensen NH, Kuijer MB, Matos RC, Tran TB. Predicting new molecular targets for known drugs. Nature. 2009;462(7270):175\u201381.","journal-title":"Nature"},{"key":"658_CR27","doi-asserted-by":"crossref","unstructured":"Chen H, Zhang H, Zhang Z, Cao Y, Tang W. Network-based inference methods for drug repositioning. Comput Math Methods Med. 2015;2015.","DOI":"10.1155\/2015\/130620"},{"issue":"5","key":"658_CR28","doi-asserted-by":"publisher","first-page":"114","DOI":"10.1186\/s12859-018-2102-9","volume":"19","author":"J Peng","year":"2018","unstructured":"Peng J, Hui W, Shang X. Measuring phenotype-phenotype similarity through the interactome. BMC bioinformatics. 2018;19(5):114.","journal-title":"BMC bioinformatics"},{"key":"658_CR29","first-page":"8","volume":"1","author":"X Zeng","year":"2018","unstructured":"Zeng X, Liu L, L\u00fc L, Zou Q, Valencia A. Prediction of potential disease-associated microRNAs using structural perturbation method. Bioinformatics. 2018;1:8.","journal-title":"Bioinformatics"},{"issue":"5","key":"658_CR30","doi-asserted-by":"publisher","first-page":"e1002503","DOI":"10.1371\/journal.pcbi.1002503","volume":"8","author":"F Cheng","year":"2012","unstructured":"Cheng F, Liu C, Jiang J, Lu W, Li W, Liu G, Zhou W, Huang J, Tang Y. Prediction of drug-target interactions and drug repositioning via network-based inference. PLoS Comput Biol. 2012;8(5):e1002503.","journal-title":"PLoS Comput Biol"},{"issue":"Suppl 5","key":"658_CR31","doi-asserted-by":"publisher","first-page":"S6","DOI":"10.1186\/1752-0509-7-S5-S6","volume":"7","author":"C Wu","year":"2013","unstructured":"Wu C, Gudivada RC, Aronow BJ, Jegga AG. Computational drug repositioning through heterogeneous network clustering. BMC Syst Biol. 2013;7(Suppl 5):S6.","journal-title":"BMC Syst Biol"},{"issue":"3","key":"658_CR32","first-page":"S4","volume":"6","author":"Y-F Huang","year":"2013","unstructured":"Huang Y-F, Yeh H-Y, Soo V-W. Inferring drug-disease associations from integration of chemical, genomic and phenotype data using network propagation. BMC Med Genet. 2013;6(3):S4.","journal-title":"BMC Med Genet"},{"issue":"17","key":"658_CR33","doi-asserted-by":"publisher","first-page":"2664","DOI":"10.1093\/bioinformatics\/btw228","volume":"32","author":"H Luo","year":"2016","unstructured":"Luo H, Wang J, Li M, Luo J, Peng X, Wu FX, Pan Y. Drug repositioning based on comprehensive similarity measures and bi-random walk algorithm. Bioinformatics. 2016;32(17):2664\u201371.","journal-title":"Bioinformatics"},{"key":"658_CR34","unstructured":"Wang W, Yang S, Li J. Drug target predictions based on heterogeneous graph inference. In: Pacific Symposium on Biocomputing Pacific Symposium on Biocomputing: NIH Public Access; 2013. p. 53."},{"issue":"4","key":"658_CR35","doi-asserted-by":"publisher","first-page":"460","DOI":"10.1093\/bib\/bbs018","volume":"13","author":"U Hahn","year":"2012","unstructured":"Hahn U, Cohen KB, Garten Y, Shah NH. Mining the pharmacogenomics literature\u2014a survey of the state of the art. Brief Bioinform. 2012;13(4):460\u201394.","journal-title":"Brief Bioinform"},{"issue":"9","key":"658_CR36","doi-asserted-by":"publisher","first-page":"e1000943","DOI":"10.1371\/journal.pcbi.1000943","volume":"6","author":"R Frijters","year":"2010","unstructured":"Frijters R, Van Vugt M, Smeets R, Van Schaik R, De Vlieg J, Alkema W. Literature mining for the discovery of hidden connections between drugs, genes and diseases. PLoS Comput Biol. 2010;6(9):e1000943.","journal-title":"PLoS Comput Biol"},{"key":"658_CR37","doi-asserted-by":"crossref","unstructured":"Yang HT, Ju JH, Wong YT, Shmulevich I, Chiang JH. Literature-based discovery of new candidates for drug repurposing. Brief Bioinform. 2016.","DOI":"10.1093\/bib\/bbw030"},{"issue":"7","key":"658_CR38","doi-asserted-by":"publisher","first-page":"e1002574","DOI":"10.1371\/journal.pcbi.1002574","volume":"8","author":"B Chen","year":"2012","unstructured":"Chen B, Ding Y, Wild DJ. Assessing drug target association using semantic linked data. PLoS Comput Biol. 2012;8(7):e1002574.","journal-title":"PLoS Comput Biol"},{"issue":"10","key":"658_CR39","doi-asserted-by":"publisher","first-page":"2479","DOI":"10.1109\/TKDE.2013.2297920","volume":"26","author":"C Shi","year":"2014","unstructured":"Shi C, Kong X, Huang Y, Philip SY, Wu B. Hetesim: a general framework for relevance measure in heterogeneous networks. Ieee T Knowl Data En. 2014;26(10):2479\u201392.","journal-title":"Ieee T Knowl Data En"},{"key":"658_CR40","doi-asserted-by":"crossref","unstructured":"Li C, Sun J, Xiong Y, Zheng G: An efficient drug-target interaction mining algorithm in heterogeneous biological networks. In: Pacific-Asia Conference on Knowledge Discovery and Data Mining: 2014. Springer: 65\u201376.","DOI":"10.1007\/978-3-319-13186-3_7"},{"key":"658_CR41","doi-asserted-by":"crossref","unstructured":"Yang J, Li A, Ge M, Wang M. Prediction of interactions between lncRNA and protein by using relevance search in a heterogeneous lncRNA-protein network. In: Control Conference (CCC): 34th Chinese: 2015. IEEE; 2015. p. 8540\u20134.","DOI":"10.1109\/ChiCC.2015.7260990"},{"key":"658_CR42","doi-asserted-by":"crossref","unstructured":"Zeng X, Liao Y, Liu Y, et al. Prediction and validation of disease genes using HeteSim Scores[J]. IEEE\/ACM Transactions on Computational Biology and Bioinformatics (TCBB). 2017;14(3):687-95.","DOI":"10.1109\/TCBB.2016.2520947"},{"key":"658_CR43","doi-asserted-by":"publisher","unstructured":"X. Zhang, Q. Zou, A. Rodriguez-Paton and x. zeng, \"Meta-path methods for prioritizing candidate disease miRNAs,\" in\u00a0IEEE\/ACM Transactions on Computational Biology and Bioinformatics. https:\/\/doi.org\/10.1109\/TCBB.2017.2776280 .","DOI":"10.1109\/TCBB.2017.2776280"},{"issue":"1","key":"658_CR44","doi-asserted-by":"publisher","first-page":"39","DOI":"10.1007\/BF02289026","volume":"18","author":"L Katz","year":"1953","unstructured":"Katz L. A new status index derived from sociometric analysis. Psychometrika. 1953;18(1):39\u201343.","journal-title":"Psychometrika"},{"issue":"5","key":"658_CR45","doi-asserted-by":"publisher","first-page":"e58977","DOI":"10.1371\/journal.pone.0058977","volume":"8","author":"UM Singh-Blom","year":"2013","unstructured":"Singh-Blom UM, Natarajan N, Tewari A, Woods JO, Dhillon IS, Marcotte EM. Prediction and validation of gene-disease associations using methods inspired by social network analyses. PLoS One. 2013;8(5):e58977.","journal-title":"PLoS One"},{"issue":"5","key":"658_CR46","doi-asserted-by":"publisher","first-page":"535","DOI":"10.1038\/sj.ejhg.5201585","volume":"14","author":"MA Driel van","year":"2006","unstructured":"van Driel MA, Bruggeman J, Vriend G, Brunner HG, Leunissen JA. A text-mining analysis of the human phenome. Eur J Hum Genet : EJHG. 2006;14(5):535\u201342.","journal-title":"Eur J Hum Genet : EJHG"},{"issue":"suppl 1","key":"658_CR47","first-page":"D514","volume":"33","author":"A Hamosh","year":"2005","unstructured":"Hamosh A, Scott AF, Amberger JS, Bocchini CA, McKusick VA. Online Mendelian inheritance in man (OMIM), a knowledgebase of human genes and genetic disorders. Nucleic Acids Res. 2005;33(suppl 1):D514\u20137.","journal-title":"Nucleic Acids Res"},{"issue":"1","key":"658_CR48","doi-asserted-by":"publisher","first-page":"e1000641","DOI":"10.1371\/journal.pcbi.1000641","volume":"6","author":"O Vanunu","year":"2010","unstructured":"Vanunu O, Magger O, Ruppin E, Shlomi T, Sharan R. Associating genes and protein complexes with disease via network propagation. PLoS Comput Biol. 2010;6(1):e1000641.","journal-title":"PLoS Comput Biol"},{"issue":"suppl_1","key":"658_CR49","doi-asserted-by":"publisher","first-page":"D901","DOI":"10.1093\/nar\/gkm958","volume":"36","author":"DS Wishart","year":"2008","unstructured":"Wishart DS, Knox C, Guo AC, Cheng D, Shrivastava S, Tzur D, Gautam B, Hassanali M. DrugBank: a knowledgebase for drugs, drug actions and drug targets. Nucleic Acids Res. 2008;36(suppl_1):D901\u20136.","journal-title":"Nucleic Acids Res"},{"key":"658_CR50","doi-asserted-by":"publisher","first-page":"81","DOI":"10.1016\/j.neucom.2015.11.109","volume":"206","author":"J Yang","year":"2016","unstructured":"Yang J, Li A, Ge M, Wang M. Relevance search for predicting lncRNA-protein interactions based on heterogeneous network. Neurocomputing. 2016;206:81\u20138.","journal-title":"Neurocomputing"},{"key":"658_CR51","doi-asserted-by":"publisher","first-page":"3664","DOI":"10.1038\/s41598-017-03986-1","volume":"7","author":"Y Xiao","year":"2017","unstructured":"Xiao Y, Zhang J, Deng L. Prediction of lncRNA-protein interactions using HeteSim scores based on heterogeneous networks. Sci Rep. 2017;7:3664.","journal-title":"Sci Rep"},{"issue":"5","key":"658_CR52","doi-asserted-by":"publisher","first-page":"369","DOI":"10.1097\/00005072-199805000-00001","volume":"57","author":"JPG Vonsattel","year":"1998","unstructured":"Vonsattel JPG, DiFiglia M. Huntington disease. J Neuropathol Exp Neurol. 1998;57(5):369.","journal-title":"J Neuropathol Exp Neurol"},{"issue":"9557","key":"658_CR53","doi-asserted-by":"publisher","first-page":"218","DOI":"10.1016\/S0140-6736(07)60111-1","volume":"369","author":"FO Walker","year":"2007","unstructured":"Walker FO. Huntington\u2019s disease. Lancet. 2007;369(9557):218\u201328.","journal-title":"Lancet"},{"issue":"1","key":"658_CR54","doi-asserted-by":"publisher","first-page":"70","DOI":"10.1176\/appi.psy.47.1.70","volume":"47","author":"M Alpay","year":"2006","unstructured":"Alpay M, Koroshetz WJ. Quetiapine in the treatment of behavioral disturbances in patients with Huntington\u2019s disease. Psychosomatics. 2006;47(1):70\u20132.","journal-title":"Psychosomatics"},{"issue":"6","key":"658_CR55","doi-asserted-by":"publisher","first-page":"441","DOI":"10.1034\/j.1600-0404.2002.01197.x","volume":"105","author":"D Paleacu","year":"2002","unstructured":"Paleacu D, Anca M, Giladi N. Olanzapine in Huntington's disease. Acta Neurol Scand. 2002;105(6):441\u20134.","journal-title":"Acta Neurol Scand"},{"issue":"3","key":"658_CR56","doi-asserted-by":"publisher","first-page":"e0173872","DOI":"10.1371\/journal.pone.0173872","volume":"12","author":"H Gelderblom","year":"2017","unstructured":"Gelderblom H, W\u00fcstenberg T, McLean T, M\u00fctze L, Fischer W, Saft C, Hoffmann R, S\u00fcssmuth S, Schlattmann P, van Duijn E. Bupropion for the treatment of apathy in Huntington\u2019s disease: a multicenter, randomised, double-blind, placebo-controlled, prospective crossover trial. PLoS One. 2017;12(3):e0173872.","journal-title":"PLoS One"}],"container-title":["BMC Systems Biology"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1186\/s12918-018-0658-7.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/article\/10.1186\/s12918-018-0658-7\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1186\/s12918-018-0658-7.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,9,12]],"date-time":"2023-09-12T15:34:42Z","timestamp":1694532882000},"score":1,"resource":{"primary":{"URL":"https:\/\/bmcsystbiol.biomedcentral.com\/articles\/10.1186\/s12918-018-0658-7"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2018,12]]},"references-count":56,"journal-issue":{"issue":"S9","published-print":{"date-parts":[[2018,12]]}},"alternative-id":["658"],"URL":"https:\/\/doi.org\/10.1186\/s12918-018-0658-7","relation":{},"ISSN":["1752-0509"],"issn-type":[{"value":"1752-0509","type":"electronic"}],"subject":[],"published":{"date-parts":[[2018,12]]},"assertion":[{"value":"31 December 2018","order":1,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"There are no ethics issues. No human participants or individual clinical data are involved with this study.","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"}},{"value":"Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.","order":4,"name":"Ethics","group":{"name":"EthicsHeading","label":"Publisher\u2019s Note"}}],"article-number":"134"}}