{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,7,9]],"date-time":"2024-07-09T16:38:29Z","timestamp":1720543109387},"reference-count":4,"publisher":"Springer Science and Business Media LLC","issue":"S1","license":[{"start":{"date-parts":[[2013,3,1]],"date-time":"2013-03-01T00:00:00Z","timestamp":1362096000000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/2.0"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["J Cheminform"],"published-print":{"date-parts":[[2013,3]]},"DOI":"10.1186\/1758-2946-5-s1-p30","type":"journal-article","created":{"date-parts":[[2013,3,22]],"date-time":"2013-03-22T11:15:28Z","timestamp":1363950928000},"source":"Crossref","is-referenced-by-count":2,"title":["The influence of training actives\/inactives ratio on machine learning performance"],"prefix":"10.1186","volume":"5","author":[{"given":"Rafa\u0142","family":"Kurczab","sequence":"first","affiliation":[]},{"given":"Sabina","family":"Smusz","sequence":"additional","affiliation":[]},{"given":"Andrzej J","family":"Bojarski","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2013,3,22]]},"reference":[{"key":"426_CR1","doi-asserted-by":"publisher","first-page":"332","DOI":"10.2174\/138620709788167980","volume":"12","author":"JL Melville","year":"2009","unstructured":"Melville JL, Burke EK, Hirst JD: Machine learning in virtual screening. Comb Chem & High Thr Scr. 2009, 12: 332-343.","journal-title":"Comb Chem & High Thr Scr"},{"key":"426_CR2","doi-asserted-by":"publisher","first-page":"1227","DOI":"10.1021\/ci800022e","volume":"48","author":"XH Ma","year":"2008","unstructured":"Ma XH, Wang R, Yang SY, Li R, Xue Y, Wei YC, Low BC, Chen YZ: Evaluation of virtual screening performance of support vector machines trained by sparsely distributed active compounds. J Chem Inf Mod. 2008, 48: 1227-1237. 10.1021\/ci800022e.","journal-title":"J Chem Inf Mod"},{"key":"426_CR3","doi-asserted-by":"publisher","first-page":"1098","DOI":"10.1021\/ci050519k","volume":"46","author":"D Plewczynski","year":"2006","unstructured":"Plewczynski D, Spieser SH, Koch U: Assessing different classification methods for virtual screening. J Chem Inf Mod. 2006, 46: 1098-106. 10.1021\/ci050519k.","journal-title":"J Chem Inf Mod"},{"issue":"1","key":"426_CR4","doi-asserted-by":"publisher","first-page":"10","DOI":"10.1145\/1656274.1656278","volume":"11","author":"M Hall","year":"2009","unstructured":"Hall M, Frank E, Holmes G, Pfahringer B, Reutemann P, Witten IH: The WEKA data mining software: an update. SIGKDD Explorations. 2009, 11 (1): 10-18. 10.1145\/1656274.1656278.","journal-title":"SIGKDD Explorations"}],"container-title":["Journal of Cheminformatics"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1186\/1758-2946-5-S1-P30.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/article\/10.1186\/1758-2946-5-S1-P30\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1186\/1758-2946-5-S1-P30.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2019,6,24]],"date-time":"2019-06-24T13:51:06Z","timestamp":1561384266000},"score":1,"resource":{"primary":{"URL":"https:\/\/jcheminf.biomedcentral.com\/articles\/10.1186\/1758-2946-5-S1-P30"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2013,3]]},"references-count":4,"journal-issue":{"issue":"S1","published-print":{"date-parts":[[2013,3]]}},"alternative-id":["426"],"URL":"https:\/\/doi.org\/10.1186\/1758-2946-5-s1-p30","relation":{},"ISSN":["1758-2946"],"issn-type":[{"value":"1758-2946","type":"electronic"}],"subject":[],"published":{"date-parts":[[2013,3]]},"article-number":"P30"}}