LinkDirectedGraph

Discovery of binding motifs and epitopes is critical in detection of cancers in early stages. Considerable efforts have been focused on introducing methods to discover regulatory motifs. However, those methods face serious challenges when dealing with NGS data: many of them are not scalable for large data sets, require prior knowledge about the number of motifs to identify, and have low accuracy. In this paper, we propose a novel approach which relies on results from theory of intersection graphs.