Artículo
GIAO C-H COSY Simulations Merged with Artificial Neural Networks Pattern Recognition Analysis. Pushing the Structural Validation a Step Forward
Fecha de publicación:
10/2015
Editorial:
American Chemical Society
Revista:
Journal of Organic Chemistry
ISSN:
0022-3263
Idioma:
Inglés
Tipo de recurso:
Artículo publicado
Clasificación temática:
Resumen
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.
Palabras clave:
Artificial Neural Networks
,
Structural Validation
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Licencia
Identificadores
Colecciones
Articulos(IQUIR)
Articulos de INST.DE QUIMICA ROSARIO
Articulos de INST.DE QUIMICA ROSARIO
Citación
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
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