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1: J Chem Inf Comput Sci. 1998 Jul-Aug;38(4):660-8.Links

Application of a pruning algorithm to optimize artificial neural networks for pharmaceutical fingerprinting.

Tetko IV, Villa AE, Aksenova TI, Zielinski WL, Brower J, Collantes ER, Welsh WJ.

Department of Biomedical Applications, Institute of Bioorganic and Petroleum Chemistry, Kiev, Ukraine.

The present study investigates an application of artificial neural networks (ANNs) for use in pharmaceutical fingerprinting. Several pruning algorithms were applied to decrease the dimension of the input parameter data set. A localized fingerprint region was identified within the original input parameter space from which a subset of input parameters was extracted leading to enhanced ANN performance. The present results confirm that ANNs can provide a fast, accurate, and consistent methodology applicable to pharmaceutical fingerprinting.

PMID: 9691475 [PubMed - indexed for MEDLINE]