2003 | OriginalPaper | Buchkapitel
Prediction and Discrimination of Pharmacological Activity by Using Artificial Neural Networks
verfasst von : M. J. Castro, W. Díaz, P. Aibar, J. L. Domínguez
Erschienen in: Pattern Recognition and Image Analysis
Verlag: Springer Berlin Heidelberg
Enthalten in: Professional Book Archive
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The design of new medical drugs is a very complex process in which combinatorial chemistry techniques are used. For this reason, it is very useful to have tools to predict and to discriminate the pharmacological activity of a given molecular compound so that the laboratory experiments can be directed to those molecule groups in which there is a high probability of finding new compounds with the desired properties. This work presents an application of Artificial Neural Networks to the problem of discriminating and predicting pharmacological characteristics of a molecular compound from its topological properties. A large amount of different configurations are tested, yielding very good performances.