A self-organizing feature map for clustering nucleic acids - Application to a data matrix containing A-DNA and B-DNA dinucleotides

A self-organizing feature map to cluster DNA dinucleotides is presented. During a training session 244 training patterns, each consisting of nine torsion angles, are clustered in a 10 by 10 map. The method is successful for separating the four known DNA classes in the training set. Contour plots of the weights after a training session indicate gradients in torsion angles corresponding to class separation. Moreover, certain units in the map probably correspond to unfavourable torsion angle combinations resulting in, e.g. van der Waals clashes. Hence, although no direct relation to a conformation's energy (as in a Ramachandran plot) is present in the map, it may provide a multidimensional interpretation of accessible and forbidden areas for dinucleotides. The applicability of the method on this DNA data matrix shows its potential to be used in more extensive structural analysis studies, e.g. in a case of comparing DNA with RNA. Several test patterns resulting from molecules with unusual structural characteristics are identified with the map. Copyright (C) 1998 Elsevier Science Ltd.