@ARTICLE{SchSchMikLaaSueGanHeiMue07a, author = {Schroeter, Timon and Schwaighofer, Anton and Mika, Sebastian and ter Laak, Antonius and S{\"u}lzle, Detlev and Ganzer, Ursula and Heinrich, Nikolaus and M{\"u}ller, Klaus-Robert}, title = "Predicting Lipophilicity of Drug Discovery Molecules using Gaussian Process Models", journal = "ChemMedChem", year = "2007", volume = "2", pages = "1265--1267", number = "9", abstract = "The lipophilicity of 14.556 library compounds at Bayer Schering was modeled using Gaussian process methodology. In a blind test with 7013 new drug-discovery molecules from the last few months, 81 \\% were predicted correctly within one log unit, compared with only 44 \\% achieved by commercial software. Predicted error bars exhibit close to ideal statistical properties, thereby allowing assessment of the model's domain of applicability.", pdf = "http://doc.ml.tu-berlin.de/publications/publications/Schroeter\_Schwaighofer\_ChemMedChem\_2007\_draft.pdf", url = "http://dx.doi.org/10.1002/cmdc.200700041" }