Consensual classification of drug and nondrug compounds
by Ayca C. Pehlivanli, Turgay Ibrikci, Okan K. Ersoy
International Journal of Computational Biology and Drug Design (IJCBDD), Vol. 1, No. 3, 2008

Abstract: A special consensual approach is discussed for separating a molecular group with a proven pharmacological activity from another molecular group without any activity. It is mainly a group decision to produce a consensus of multiple classification results obtained with a single classification algorithm. For this purpose, the constructed model has a preprocessing unit which consists of transformation of input patterns by random matrices and median filtering to generate independent errors for a single type of classifier and postprocessing for consensus. The neural network based consensus classifier operating with MOE descriptors was applied to a set of 641 chemical structures. The confirmed drugs were classified with an accuracy of 86.54% while nondrugs resulted in 82.67% accuracy.

Online publication date: Wed, 26-Nov-2008

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