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dc.rights.licensehttp://creativecommons.org/licenses/by/4.0es_MX
dc.creatorKarina Martínez-Mayorga-
dc.date.accessioned2018-11-26T15:53:20Z-
dc.date.available2018-11-26T15:53:20Z-
dc.date.issued2017-
dc.identifier.urihttp://rdu.iquimica.unam.mx/handle/20.500.12214/1152-
dc.description.abstractHerein is proposed a general approach to represent an entire compound library with a single binary fingerprint. The development of the database fingerprint (DFP) is illustrated first using a short fingerprint (MACCS keys) for 10 data sets of general interest in chemistry. The application of the DFP is further shown with PubChem fingerprints for the data sets used in the primary example but with a larger number of compounds, up to 25,000 molecules. The performance of DFP were studied through differential Shannon entropy, k-mean clustering, and DFP/Tanimoto similarity.es_MX
dc.language.isoenges_MX
dc.rightsinfo:eu-repo/semantics/openAccesses_MX
dc.sourceJournal of Cheminformatics (ISSN: 1758-2946) 9, 9es_MX
dc.titleDatabase fingerprint (DFP): an approach to represent molecular databaseses_MX
dc.typeinfo:eu-repo/semantics/articlees_MX
dc.creator.idinfo:eu-repo/dai/mx/orcid/0000-0002-6974-7941es_MX
dc.relation.alternativeidentifierhttps://doi.org/10.1186/s13321-017-0195-1-
dc.subject.ctiinfo:eu-repo/classification/cti/2es_MX
dc.subject.keywordsDiversityes_MX
dc.subject.keywordsInformation contentes_MX
dc.subject.keywordsMolecular fingerprintses_MX
dc.subject.keywordsSimilarityes_MX
dc.subject.keywordsShannon entropyes_MX
dc.creator.twoJose Medina_Franco-
dc.creator.idtwoinfo:eu-repo/dai/mx/orcid/0000-0003-4940-1107es_MX
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