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dc.contributor.author
Zanardi, Maria Marta  
dc.contributor.author
Sarotti, Ariel Marcelo  
dc.date.available
2018-07-17T15:33:01Z  
dc.date.issued
2015-10  
dc.identifier.citation
Zanardi, Maria Marta; Sarotti, Ariel Marcelo; GIAO C-H COSY Simulations Merged with Artificial Neural Networks Pattern Recognition Analysis. Pushing the Structural Validation a Step Forward; American Chemical Society; Journal of Organic Chemistry; 80; 19; 10-2015; 9371-9378  
dc.identifier.issn
0022-3263  
dc.identifier.uri
http://hdl.handle.net/11336/52389  
dc.description.abstract
The structural validation problem using quantum chemistry approaches (confirm or reject a candidate structure) has been tackled with artificial neural network (ANN) mediated multidimensional pattern recognition from experimental and calculated 2D C-H COSY. In order to identify subtle errors (such as regio- or stereochemical), more than 400 ANNs have been built and trained, and the most efficient in terms of classification ability were successfully validated in challenging real examples of natural product misassignments.  
dc.format
application/pdf  
dc.language.iso
eng  
dc.publisher
American Chemical Society  
dc.rights
info:eu-repo/semantics/openAccess  
dc.rights.uri
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/  
dc.subject
Artificial Neural Networks  
dc.subject
Structural Validation  
dc.subject.classification
Otras Ciencias Químicas  
dc.subject.classification
Ciencias Químicas  
dc.subject.classification
CIENCIAS NATURALES Y EXACTAS  
dc.title
GIAO C-H COSY Simulations Merged with Artificial Neural Networks Pattern Recognition Analysis. Pushing the Structural Validation a Step Forward  
dc.type
info:eu-repo/semantics/article  
dc.type
info:ar-repo/semantics/artículo  
dc.type
info:eu-repo/semantics/publishedVersion  
dc.date.updated
2018-07-17T13:57:21Z  
dc.journal.volume
80  
dc.journal.number
19  
dc.journal.pagination
9371-9378  
dc.journal.pais
Estados Unidos  
dc.description.fil
Fil: Zanardi, Maria Marta. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Rosario. Instituto de Química Rosario. Universidad Nacional de Rosario. Facultad de Ciencias Bioquímicas y Farmacéuticas. Instituto de Química Rosario; Argentina  
dc.description.fil
Fil: Sarotti, Ariel Marcelo. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Rosario. Instituto de Química Rosario. Universidad Nacional de Rosario. Facultad de Ciencias Bioquímicas y Farmacéuticas. Instituto de Química Rosario; Argentina  
dc.journal.title
Journal of Organic Chemistry  
dc.relation.alternativeid
info:eu-repo/semantics/altIdentifier/doi/http://dx.doi.org/10.1021/acs.joc.5b01663  
dc.relation.alternativeid
info:eu-repo/semantics/altIdentifier/url/https://pubs.acs.org/doi/full/10.1021/acs.joc.5b01663  

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