Graph pattern matching is a central problem in many application fields, and may be associated with problems in bioinformatics, such as finding patterns in biochemical networks. This problem can be view as a particular case of labelled subgraph isomorphism (SGI). In this paper, we focus on a constraint programming approach. Two new constraints are introduced to solve this problem. We consider labelled graphs, especially suited for representing biochemical networks, and we propose a constraint exploiting this information. Another constraint considers neighbors within k steps, generalizing the simple neighbor constraint. Experimental results show the potential benefit of the constraints when integrated in a backtracking-based constraint system.
Zampelli, S., Deville, Y., & Dupont, P. (2004). Finding Patterns in Biochemical Networks. 5h Open Days in Biology, Computer Science and Mathematics (JOBIM 2004), Montreal, Canada. https://hdl.handle.net/2078.5/226256