{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,31]],"date-time":"2026-03-31T21:24:24Z","timestamp":1774992264548,"version":"3.50.1"},"reference-count":26,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2013,9,24]],"date-time":"2013-09-24T00:00:00Z","timestamp":1379980800000},"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":[[2013,12]]},"DOI":"10.1186\/1758-2946-5-43","type":"journal-article","created":{"date-parts":[[2013,9,24]],"date-time":"2013-09-24T20:09:28Z","timestamp":1380053368000},"source":"Crossref","is-referenced-by-count":174,"title":["Similarity maps - a visualization strategy for molecular fingerprints and machine-learning methods"],"prefix":"10.1186","volume":"5","author":[{"given":"Sereina","family":"Riniker","sequence":"first","affiliation":[]},{"given":"Gregory A","family":"Landrum","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2013,9,24]]},"reference":[{"key":"484_CR1","doi-asserted-by":"publisher","first-page":"1115","DOI":"10.1126\/science.132.3434.1115","volume":"132","author":"D Rogers","year":"1960","unstructured":"Rogers D, Tanimoto TT: A computer program for classifying plants. Science. 1960, 132: 1115-1118. 10.1126\/science.132.3434.1115.","journal-title":"Science"},{"key":"484_CR2","doi-asserted-by":"publisher","first-page":"297","DOI":"10.2307\/1932409","volume":"26","author":"LR Dice","year":"1945","unstructured":"Dice LR: Measures of the amount of ecological association between species. Ecology. 1945, 26: 297-302. 10.2307\/1932409.","journal-title":"Ecology"},{"key":"484_CR3","doi-asserted-by":"publisher","first-page":"817","DOI":"10.1002\/minf.201100059","volume":"30","author":"K Hansen","year":"2011","unstructured":"Hansen K, Baehrens D, Schroeter T, Rupp M, M\u00fcller KR: Visual interpretation of kernel-based prediction models. Mol Inf. 2011, 30: 817-826. 10.1002\/minf.201100059.","journal-title":"Mol Inf"},{"key":"484_CR4","doi-asserted-by":"publisher","first-page":"862","DOI":"10.1021\/ci950169+","volume":"36","author":"NE Shemetulskis","year":"1996","unstructured":"Shemetulskis NE, Weiniger D, Blankey CJ, Yang JJ, Humblet C: Stigmata: an algorithm to determine structural commonalities in diverse datasets. J Chem Inf Comput Sci. 1996, 36: 862-871. 10.1021\/ci950169+.","journal-title":"J Chem Inf Comput Sci"},{"key":"484_CR5","doi-asserted-by":"publisher","first-page":"85","DOI":"10.1016\/S1093-3263(99)00026-1","volume":"17","author":"DJ Wild","year":"1999","unstructured":"Wild DJ, Blankley CJ: VisualiSAR: a web-based application for clustering, structure browsing, and structure-activity relationship study. J Mol Graph Model. 1999, 17: 85-89. 10.1016\/S1093-3263(99)00026-1.","journal-title":"J Mol Graph Model"},{"key":"484_CR6","doi-asserted-by":"publisher","first-page":"6997","DOI":"10.1021\/jm050619h","volume":"48","author":"L Franke","year":"2005","unstructured":"Franke L, Byvatov E, Werz O, Steinhilber D, Schneider P, Schneider G: Extraction and visualization of potential pharmacophore points using support vector machines: application to ligand-based virtual screening for COX-2 inhibitors. J Med Chem. 2005, 48: 6997-7004. 10.1021\/jm050619h.","journal-title":"J Med Chem"},{"key":"484_CR7","doi-asserted-by":"publisher","first-page":"11","DOI":"10.1186\/1758-2946-3-11","volume":"3","author":"L Rosenbaum","year":"2011","unstructured":"Rosenbaum L, Hinselmann G, Jahn A, Zell A: Interpreting linear support vector machine models with heat map molecule coloring. J Cheminf. 2011, 3: 11-22. 10.1186\/1758-2946-3-11.","journal-title":"J Cheminf"},{"key":"484_CR8","doi-asserted-by":"publisher","first-page":"2144","DOI":"10.1002\/cbdv.200900148","volume":"6","author":"M Segall","year":"2009","unstructured":"Segall M, Champness E, Obrezanova O, Leeding C: Beyond profiling: using ADMET models to guide decisions. Chem Biodivers. 2009, 6: 2144-2151. 10.1002\/cbdv.200900148.","journal-title":"Chem Biodivers"},{"key":"484_CR9","unstructured":"Glowing Molecule visualization tool by Optibrium. [\n                    http:\/\/www.optibrium.com\/community\/faq\/glowing-molecule\n                    \n                  ],"},{"key":"484_CR10","unstructured":"RDKit: Cheminformatics and Machine Learning Software 2013. [\n                    http:\/\/www.rdkit.org\n                    \n                  ],"},{"key":"484_CR11","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: 2825-2830.","journal-title":"J Mach Learn Res"},{"key":"484_CR12","doi-asserted-by":"publisher","first-page":"90","DOI":"10.1109\/MCSE.2007.55","volume":"9","author":"JD Hunter","year":"2007","unstructured":"Hunter JD: Matplotlib: a 2D graphics environment. Comput Sci Eng. 2007, 9: 90-95.","journal-title":"Comput Sci Eng"},{"key":"484_CR13","doi-asserted-by":"publisher","first-page":"437","DOI":"10.1146\/annurev.pharmtox.42.091101.144224","volume":"42","author":"L Shi","year":"2002","unstructured":"Shi L, Javitch JA: The binding site of aminergic G protein-coupled receptors: the transmembrane segments and second extracellular loop. Annu Rev Pharmacol Toxicol. 2002, 42: 437-467. 10.1146\/annurev.pharmtox.42.091101.144224.","journal-title":"Annu Rev Pharmacol Toxicol"},{"key":"484_CR14","doi-asserted-by":"publisher","first-page":"1091","DOI":"10.1126\/science.1197410","volume":"330","author":"EY Chien","year":"2010","unstructured":"Chien EY, Liu W, Zhao Q, Katritch V, Han GW, Hanson MA, Shi L, Newman AH, Javitch JA, Cherezov V, Stevens RC: Structure of the human dopamine D3 receptor in complex with a D2\/D3 selective antagonist. Science. 2010, 330: 1091-1095. 10.1126\/science.1197410.","journal-title":"Science"},{"key":"484_CR15","doi-asserted-by":"publisher","first-page":"D1100\u2014D1107","DOI":"10.1093\/nar\/gkr777","volume":"40","author":"A Gaulton","year":"2012","unstructured":"Gaulton A, Bellis LJ, Bento AP, Chambers J, Davies M, Hersey A, Light Y, McGlinchey S, Michalovich D, Al-Lazikani B, Overington JP: ChEMBL: a large-scale bioactivity database for drug discovery. Nucleic Acids Res. 2012, 40: D1100\u2014D1107-","journal-title":"Nucleic Acids Res"},{"key":"484_CR16","unstructured":"ChEMBL: European Bioinformatics Institute (EBI), version 14. Cambridge, UK. 2012, [\n                    http:\/\/www.ebi.ac.uk\/chembl\/\n                    \n                  ],"},{"key":"484_CR17","doi-asserted-by":"publisher","first-page":"3581","DOI":"10.1021\/jm200288r","volume":"54","author":"AK Banala","year":"2011","unstructured":"Banala AK, Levy BA, Khatri SS, Furman CA, Roof RA, Mishra Y, Griffin SA, Sibley DR, Luedtke RR, Newman AH: N-(3-Fluoro-4-(4-(2-methoxy or 2,3-dichlorophenyl)piperazine-1-yl)butyl)arylcarboxamides as selective dopamine D3 receptor ligands: critical role of the carboxamide linker for D3 receptor selectivity. J Med Chem. 2011, 54: 3581-3594. 10.1021\/jm200288r.","journal-title":"J Med Chem"},{"key":"484_CR18","doi-asserted-by":"publisher","first-page":"358","DOI":"10.1021\/jm050734s","volume":"49","author":"M Leopoldo","year":"2006","unstructured":"Leopoldo M, Lacivita E, Giorgio PD, Colabufo NA, Niso M, Berardi F, Perrone R: Design, synthesis, and binding affinities of potential positron emission tomography (PET) ligands for visualization of brain dopamine D3 receptors. J Med Chem. 2006, 49: 358-365. 10.1021\/jm050734s.","journal-title":"J Med Chem"},{"key":"484_CR19","doi-asserted-by":"publisher","first-page":"7258","DOI":"10.1016\/j.bmc.2007.08.034","volume":"15","author":"BC Sasse","year":"2007","unstructured":"Sasse BC, Mach UR, Leppaenen J, Calmels T, Stark H: Hybrid approach for the design of highly affine and selective dopamine D3 receptor ligands using privileged scaffolds of biogenic amine GPCR ligands. Bioorg Med Chem. 2007, 15: 7258-7273. 10.1016\/j.bmc.2007.08.034.","journal-title":"Bioorg Med Chem"},{"key":"484_CR20","doi-asserted-by":"publisher","first-page":"64","DOI":"10.1021\/ci00046a002","volume":"25","author":"RE Carhart","year":"1985","unstructured":"Carhart RE, Smith DH, Venkataraghavan R: Atom pairs as molecular features in structure-activity studies: definition and applications. J Chem Inf Comput Sci. 1985, 25: 64-73. 10.1021\/ci00046a002.","journal-title":"J Chem Inf Comput Sci"},{"key":"484_CR21","doi-asserted-by":"publisher","first-page":"742","DOI":"10.1021\/ci100050t","volume":"50","author":"D Rogers","year":"2010","unstructured":"Rogers D, Hahn M: Extended-connectivity fingerprints. J Chem Inf Model. 2010, 50: 742-754. 10.1021\/ci100050t.","journal-title":"J Chem Inf Model"},{"key":"484_CR22","doi-asserted-by":"publisher","first-page":"26","DOI":"10.1186\/1758-2946-5-26","volume":"5","author":"S Riniker","year":"2013","unstructured":"Riniker S, Landrum G: Open source platform to benchmark fingerprints for ligand-based virtual screening. J Cheminf. 2013, 5: 26-10.1186\/1758-2946-5-26.","journal-title":"J Cheminf"},{"issue":"Suppl 1","key":"484_CR23","doi-asserted-by":"publisher","first-page":"O3","DOI":"10.1186\/1758-2946-3-S1-O3","volume":"3","author":"G Landrum","year":"2011","unstructured":"Landrum G, Lewis R, Palmer A, Stiefl N, Vulpetti A: Making sure there\u2019s a \"give\" associated with the \"take\": producing and using open-source software in big pharma. J Cheminf. 2011, 3 (Suppl 1): O3-10.1186\/1758-2946-3-S1-O3.","journal-title":"J Cheminf"},{"key":"484_CR24","doi-asserted-by":"publisher","first-page":"47","DOI":"10.1002\/(SICI)1097-0290(199824)61:1<47::AID-BIT9>3.0.CO;2-Z","volume":"61","author":"A Gobbi","year":"1998","unstructured":"Gobbi A, Poppinger D: Genetic optimization of combinatorial libraries. Biotech Bioeng. 1998, 61: 47-54. 10.1002\/(SICI)1097-0290(199824)61:1<47::AID-BIT9>3.0.CO;2-Z.","journal-title":"Biotech Bioeng"},{"key":"484_CR25","doi-asserted-by":"publisher","first-page":"771","DOI":"10.1021\/ci100062n","volume":"50","author":"M Sastry","year":"2010","unstructured":"Sastry M, Lowrie JF, Dixon SL, Sherman W: Large-scale systematic analysis of 2D fingerprint methods and parameters to improve virtual screening enrichments. J Chem Inf Model. 2010, 50: 771-784. 10.1021\/ci100062n.","journal-title":"J Chem Inf Model"},{"key":"484_CR26","volume-title":"Using Random Forest to Learn Imbalanced Data","author":"C Chen","year":"2004","unstructured":"Chen C, Liaw A, Breiman L: Using Random Forest to Learn Imbalanced Data. 2004, Berkeley: University of California"}],"container-title":["Journal of Cheminformatics"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1186\/1758-2946-5-43.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/article\/10.1186\/1758-2946-5-43\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1186\/1758-2946-5-43.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2019,6,24]],"date-time":"2019-06-24T14:34:17Z","timestamp":1561386857000},"score":1,"resource":{"primary":{"URL":"https:\/\/jcheminf.biomedcentral.com\/articles\/10.1186\/1758-2946-5-43"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2013,9,24]]},"references-count":26,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2013,12]]}},"alternative-id":["484"],"URL":"https:\/\/doi.org\/10.1186\/1758-2946-5-43","relation":{},"ISSN":["1758-2946"],"issn-type":[{"value":"1758-2946","type":"electronic"}],"subject":[],"published":{"date-parts":[[2013,9,24]]},"article-number":"43"}}