GIAO C–H COSY Simulations Merged with Artificial Neural Networks Pattern Recognition Analysis. Pushing the Structural Validation a Step Forward | Zendy

Marı́a M. Zanardi | Zendy; Ariel M. Sarotti | Zendy

Open Access

GIAO C–H COSY Simulations Merged with Artificial Neural Networks Pattern Recognition Analysis. Pushing the Structural Validation a Step Forward

Author(s) -

Marı́a M. Zanardi,

Ariel M. Sarotti

Publication year - 2015

Publication title -

the journal of organic chemistry

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 1.2

H-Index - 228

eISSN - 1520-6904

pISSN - 0022-3263

DOI - 10.1021/acs.joc.5b01663

Subject(s) - artificial neural network , artificial intelligence , computer science , pattern recognition (psychology) , deep neural networks , biological system , biology

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.

The content you want is available to Zendy users.

Already have an account? Click here to sign in.

Having issues? You can contact us here

Accelerating Research