Prediction of liquid chromatographic retention behavior based on quantum chemical parameters using supervised self organizing maps

► A supervised SOM was applied to predict chromatographic retention behavior. ► The proposed algorithm is simple and requires only a small tweak of a standard SOM. ► The method was applied to two data sets to demonstrate its application. ► The advantage is that non-linear structure of the model can be revealed.