English   español  
Please use this identifier to cite or link to this item: http://hdl.handle.net/10261/86561
Share/Impact:
Statistics
logo share SHARE logo core CORE   Add this article to your Mendeley library MendeleyBASE

Visualizar otros formatos: MARC | Dublin Core | RDF | ORE | MODS | METS | DIDL | DATACITE
Exportar a otros formatos:

Title

Neural computational prediction of oral drug absorption based on CODES 2D descriptors

AuthorsGuerra, Ángela CSIC; Campillo, Nuria E. CSIC ORCID ; Páez, Juan A. CSIC ORCID
Issue Date2010
PublisherElsevier
CitationEuropean Journal of Medicinal Chemistry 45: 930- 940 (2010)
AbstractA neural model based on a numerical molecular representation using CODES® program to predict oral absorption of any structure is described. This model predicts both high and low-absorbed compounds with a global accuracy level of 74%. CODES/ANN methodology shows promising utilities not only as a conventional in silico tool in high-throughput screening or improvement of absorption capabilities procedures but also the improvement of in vitro-in vivo correlation could be addressed. © 2009 Elsevier Masson SAS. All rights reserved.
URIhttp://hdl.handle.net/10261/86561
DOIhttp://dx.doi.org/10.1016/j.ejmech.2009.11.034
Identifiersdoi: 10.1016/j.ejmech.2009.11.034
issn: 0223-5234
e-issn: 1768-3254
Appears in Collections:(IQM) Artículos
Files in This Item:
File Description SizeFormat 
accesoRestringido.pdf15,38 kBAdobe PDFThumbnail
View/Open
Show full item record
Review this work
 

Related articles:


WARNING: Items in Digital.CSIC are protected by copyright, with all rights reserved, unless otherwise indicated.