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Up to now, a variety of benchmarking data sets had been generated and frequently used. Among them, MUBD\u2010HDACs from our prior research efforts was regarded as one of five state\u2010of\u2010the\u2010art benchmarks in 2017 by <jats:italic>Frontiers in Pharmacology<\/jats:italic>. This benchmarking set was generated by one of our unique de\u2010biasing algorithms. It also rendered quite a few other cases of successful applications in recent years, thus is expected to have more impact in modern drug discovery. To make our algorithm amenable to more users, we developed a Python GUI application called MUBD\u2010DecoyMaker 2.0. Moreover, it has two new additional functional modules, i.\u2009e. \u201cDetect 2D Bias\u201d and \u201cQuality Control\u201d. This new GUI version had been proved to be easy to use while generate benchmarking data sets of the same quality. MUBD\u2010DecoyMaker 2.0 is freely available at https:\/\/github.com\/jwxia2014\/MUBD\u2010DecoyMaker2.0, along with its manual and testcase.<\/jats:p>","DOI":"10.1002\/minf.201900151","type":"journal-article","created":{"date-parts":[[2019,12,12]],"date-time":"2019-12-12T08:10:23Z","timestamp":1576138223000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":12,"title":["MUBD\u2010DecoyMaker 2.0: A Python GUI Application to Generate Maximal Unbiased Benchmarking Data Sets for Virtual Drug Screening"],"prefix":"10.1002","volume":"39","author":[{"given":"Jie","family":"Xia","sequence":"first","affiliation":[{"name":"State Key Laboratory of Bioactive Substance and Function of Natural Medicines, Department of New Drug Research and Development, Institute of Materia Medica Chinese Academy of Medical Sciences and Peking Union Medical College  Beijing 100050 China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Shan","family":"Li","sequence":"additional","affiliation":[{"name":"College of Economics and Management Nanjing University of Aeronautics and Astronautics  Nanjing 211106 China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yu","family":"Ding","sequence":"additional","affiliation":[{"name":"College of Economics and Management Nanjing University of Aeronautics and Astronautics  Nanjing 211106 China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Song","family":"Wu","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Bioactive Substance and Function of Natural Medicines, Department of New Drug Research and Development, Institute of Materia Medica Chinese Academy of Medical Sciences and Peking Union Medical College  Beijing 100050 China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4156-3753","authenticated-orcid":false,"given":"Xiang Simon","family":"Wang","sequence":"additional","affiliation":[{"name":"Artificial Intelligence and Drug Discovery Core Laboratory for District of Columbia Center for AIDS Research (DC CFAR), Department of Pharmaceutical Sciences, College of Pharmacy Howard University  Washington DC 20059 U.S.A."}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"311","published-online":{"date-parts":[[2019,12,23]]},"reference":[{"key":"e_1_2_7_2_1","doi-asserted-by":"publisher","DOI":"10.1007\/s10822-008-9189-4"},{"key":"e_1_2_7_3_1","unstructured":"\u00a0"},{"key":"e_1_2_7_4_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.ymeth.2014.11.015"},{"key":"e_1_2_7_5_2","doi-asserted-by":"publisher","DOI":"10.1021\/acs.jcim.5b00090"},{"key":"e_1_2_7_6_1","doi-asserted-by":"publisher","DOI":"10.1021\/ci8002649"},{"key":"e_1_2_7_7_1","doi-asserted-by":"publisher","DOI":"10.1021\/ci2001549"},{"key":"e_1_2_7_8_1","doi-asserted-by":"publisher","DOI":"10.1021\/jm300687e"},{"key":"e_1_2_7_9_1","author":"Lagarde N.","year":"2014","journal-title":"J. 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