lassification of multiway analytical data based n MOLMAP approach

Anewmethod for the studyofmolecule chemical informationorganized into three-waydata structures (MOLMAP) was recently proposed in literature. Basically, MOLMAPmolecular fingerprints are calculated by projecting bond properties of molecules into Kohonen networks and used to generate molecular descriptors for QSAR modeling. Since this technique has never been applied to other kinds of chemical multiway data, in this study classification models were carried out by means of MOLMAP approach on three-way analytical datasets of electronic nose and fluorescence data. For comparing purposes, other classificationmethods were applied to the same datasets: Discriminant Analysis on the PARAFAC scores and Partial Least Square-Discriminant Analysis (PLS-DA) on the unfolded data. Since the MOLMAP approach provided good results for the analyzed datasets, here, we propose the MOLMAP approach to be used as a general technique for the classification of