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Please use this identifier to cite or link to this item: https://hdl.handle.net/1959.11/28208
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dc.contributor.authorAgatonovic-Kustrin, Sen
dc.contributor.authorTurner, J Ven
dc.date.accessioned2020-03-16T01:51:30Z-
dc.date.available2020-03-16T01:51:30Z-
dc.date.issued2006-
dc.identifier.citationLetters in Drug Design and Discovery, 3(7), p. 436-442en
dc.identifier.issn1875-628Xen
dc.identifier.issn1570-1808en
dc.identifier.urihttps://hdl.handle.net/1959.11/28208-
dc.description.abstractDifferential pathophysiological roles of estrogen receptors alpha (ERα) and beta (ERβ) are of particular interest for phytochemical screening. A QSAR incorporating theoretical descriptors was developed in the present study utilizing sequential multiple-output artificial neural networks. Significant steric, constitutional, topological and electronic descriptors were identified enabling ER affinity differentiation.en
dc.languageenen
dc.publisherBentham Science Publishers Ltden
dc.relation.ispartofLetters in Drug Design and Discoveryen
dc.titleArtificial Neural Network Modeling of Phytoestrogen Binding to Estrogen Receptorsen
dc.typeJournal Articleen
dc.identifier.doi10.2174/157018006778194871en
local.contributor.firstnameSen
local.contributor.firstnameJ Ven
local.subject.for2008030402 Biomolecular Modelling and Designen
local.subject.for2008030799 Theoretical and Computational Chemistry not elsewhere classifieden
local.subject.for2008030404 Cheminformatics and Quantitative Structure-Activity Relationshipsen
local.subject.seo2008860803 Human Pharmaceutical Treatments (e.g. Antibiotics)en
local.profile.schoolSchool of Rural Medicineen
local.profile.emailJoseph.Turner@une.edu.auen
local.output.categoryC1en
local.record.placeauen
local.record.institutionUniversity of New Englanden
local.publisher.placeNetherlandsen
local.format.startpage436en
local.format.endpage442en
local.identifier.scopusid33748518909en
local.peerreviewedYesen
local.identifier.volume3en
local.identifier.issue7en
local.contributor.lastnameAgatonovic-Kustrinen
local.contributor.lastnameTurneren
dc.identifier.staffune-id:jturne59en
local.profile.orcid0000-0002-0023-4275en
local.profile.roleauthoren
local.profile.roleauthoren
local.identifier.unepublicationidune:1959.11/28208en
dc.identifier.academiclevelAcademicen
dc.identifier.academiclevelAcademicen
local.title.maintitleArtificial Neural Network Modeling of Phytoestrogen Binding to Estrogen Receptorsen
local.output.categorydescriptionC1 Refereed Article in a Scholarly Journalen
local.search.authorAgatonovic-Kustrin, Sen
local.search.authorTurner, J Ven
local.istranslatedNoen
local.uneassociationNoen
local.atsiresearchNoen
local.sensitive.culturalNoen
local.identifier.wosid000240304300001en
local.year.published2006en
local.fileurl.closedpublishedhttps://rune.une.edu.au/web/retrieve/a1f671cd-e1af-4729-b381-eb5eabdf314aen
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School of Rural Medicine
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