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dc.contributor.authorMussa, Hamse Yussuf
dc.contributor.authorMitchell, John B. O.
dc.contributor.authorGlen, Robert
dc.date.accessioned2015-12-11T14:40:03Z
dc.date.available2015-12-11T14:40:03Z
dc.date.issued2015-12-01
dc.identifier.citationMussa , H Y , Mitchell , J B O & Glen , R 2015 , ' A note on utilising binary features as ligand descriptors ' , Journal of Cheminformatics , vol. 7 , 58 . https://doi.org/10.1186/s13321-015-0105-3en
dc.identifier.issn1758-2946
dc.identifier.otherPURE: 229886143
dc.identifier.otherPURE UUID: 766ce255-e45c-4a25-951b-a54374477737
dc.identifier.otherScopus: 84956875892
dc.identifier.otherORCID: /0000-0002-0379-6097/work/34033382
dc.identifier.otherWOS: 000366277900001
dc.identifier.urihttp://hdl.handle.net/10023/7905
dc.descriptionMussa and Mitchell thank the BBSRC for funding this research through grant BB/I00596X/1. Mitchell thanks the Scottish Universities Life Sciences Alliance (SULSA) for financial support.en
dc.description.abstractIt is common in cheminformatics to represent the properties of a ligand as a string of 1’s and 0’s, with the intention of elucidating, inter alia, the relationship between the chemical structure of a ligand and its bioactivity. In this commentary we note that, where relevant but non-redundant features are binary, they inevitably lead to a classifier capable of capturing only a linear relationship between structural features and activity. If, instead, we were to use relevant but non-redundant real-valued features, the resulting predictive model would be capable of describing a non-linear structure-activity relationship. Hence, we suggest that real-valued features, where available, are to be preferred in this scenario.
dc.language.isoeng
dc.relation.ispartofJournal of Cheminformaticsen
dc.rights© 2015 Mussa et al. This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.en
dc.subjectBinary descriptorsen
dc.subjectLigand chemical structureen
dc.subjectLinear relationshipen
dc.subjectBernoulli distributionen
dc.subjectQD Chemistryen
dc.subjectT-NDASen
dc.subject.lccQDen
dc.titleA note on utilising binary features as ligand descriptorsen
dc.typeJournal articleen
dc.description.versionPublisher PDFen
dc.contributor.institutionUniversity of St Andrews.School of Chemistryen
dc.contributor.institutionUniversity of St Andrews.Biomedical Sciences Research Complexen
dc.contributor.institutionUniversity of St Andrews.EaSTCHEMen
dc.identifier.doihttps://doi.org/10.1186/s13321-015-0105-3
dc.description.statusPeer revieweden
dc.identifier.urlhttp://www.jcheminf.com/content/7/1/58en


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