title: Support vector machines for the estimation of aqueous solubility.
abstract: Support Vector Machines (SVMs) are used to estimate aqueous solubility of organic compounds. A SVM equipped with a Tanimoto similarity kernel estimates solubility with accuracy comparable to results from other reported methods where the same data sets have been studied. Complete cross-validation on a diverse data set resulted in a root-mean-squared error = 0.62 and R(2) = 0.88. The data input to the machine is in the form of molecular fingerprints. No physical parameters are explicitly involved in calculations.
authors: Medivir AB, Lunastigen 7, 141 44 Huddinge, Sweden. Peter.lind@medivir.se
authors: Peter
authors: P
authors: Lind
authors: Tatiana
authors: T
authors: Maltseva