Inference of Approximated Motifs with Conserved Relations

In this paper we define a new class of problems that generalizes that of finding repeated motifs. The novelty lies in the addition of constraints on the motifs in terms of relations that must hold between pairs of positions of the motifs. We will hence denote them as "relational motifs". For this class of problems we give an algorithm that is a suitable extension of the KMR paradigm and, in particular, of the KMRC as it uses a degenerate alphabet. The algorithm contains several improvements with respect to KMRC that result especially useful when---as it is required for relational motifs---the inference is made by partially overlapping shorter motifs, rather than concatenating them like in KMR. The efficiency, correctness and completeness of the algorithm is assured by several non-trivial properties that we prove in this paper. Finally, we list some possible applications and we focus on one of them: the study of 3D structures of proteins.