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https://hdl.handle.net/1959.11/28208| Title: | Artificial Neural Network Modeling of Phytoestrogen Binding to Estrogen Receptors | Contributor(s): | Agatonovic-Kustrin, S (author); Turner, J V (author) |
Publication Date: | 2006 | DOI: | 10.2174/157018006778194871 | Handle Link: | https://hdl.handle.net/1959.11/28208 | Abstract: | Differential 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. | Publication Type: | Journal Article | Source of Publication: | Letters in Drug Design and Discovery, 3(7), p. 436-442 | Publisher: | Bentham Science Publishers Ltd | Place of Publication: | Netherlands | ISSN: | 1875-628X 1570-1808 |
Fields of Research (FoR) 2008: | 030402 Biomolecular Modelling and Design 030799 Theoretical and Computational Chemistry not elsewhere classified 030404 Cheminformatics and Quantitative Structure-Activity Relationships |
Socio-Economic Objective (SEO) 2008: | 860803 Human Pharmaceutical Treatments (e.g. Antibiotics) | Peer Reviewed: | Yes | HERDC Category Description: | C1 Refereed Article in a Scholarly Journal |
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| Appears in Collections: | Journal Article School of Rural Medicine |
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