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ISSN 2063-5346
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PREDICTION OF PREDOMINANT CONFIGURATION IN THE ENANTIOSELECTIVE REDUCTION OF -KETOACID DERIVATES WITH BAKER’S YEAST USING NEURAL NETWORKS

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Didier Villemin,[a]* Driss Cherqaoui[a] and Abdelhalim Mesbah
» doi: 10.17628/ECB.2016.5.129

Abstract

Correlation between chemical structure and enantioselectivity in baker’s yeast reduction of a set of carbonyl compounds was constructed by means of a multi-layer neural network using the back-propagation algorithm. To evaluate the predictive power of the neural network (NN) model, the cross-validation procedure was used, 88 % of the reactions were correctly predicted.

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