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A neural network-based prediction model of AR inhibitory activity from a sparse set of compounds

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4 Author(s)
Parra-Hernandez, R. ; Dept. of Electr. & Comput. Eng., Victoria Univ., Victoria, BC, Canada ; Laxdal, E.M. ; Dimopoulos, N.J. ; Alexiou, P.

In this paper, we present a mechanism to obtain a neural network-based model that predicts an enzyme inhibitory activity of a group of compounds. The mechanism selects the compounds, among a sparse set of, that should be used to obtain models of the inhibitory activity of interest. That is, the mechanism is aimed at the selection of a training set of compounds which ensures that the training of a neural network-based model results in a system capable of generalization.

Published in:

Neural Networks, 2005. IJCNN '05. Proceedings. 2005 IEEE International Joint Conference on  (Volume:4 )

Date of Conference:

July 31 2005-Aug. 4 2005

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