Abstract
The performances of a log P model designed from EVA descriptors based on theoretically derived normal coordinate frequencies and using the classical PLS analysis as statistical engine were compared to those provided by a neural network model employing various autocorrelation vectors for describing the molecules. The superiority of the latter is clearly demonstrated for simulating the lipophilicity of simple chemical structures.
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