Associated subgraph mining in biological network

In this paper, we have tried to implement a subgraph discovery method. Unlike other frequent subgraph mining methods, here we are trying to find only those subgraphs that are associated with a specific set of vertices which are biologically relevant, suggested by experts in Biotechnology, Bioinformatics, Plant System Biology etc,. Parallel processing would be an excellent solution for generating candidate subgraphs and would likely speed-up the code a great deal. So it will become necessary to work with a Breadth First Search approach (BFS) instead of a Depth First Search approach (DFS) to optimise the usage of parallel computing. Hence, traversing through the search space has been completed in a BFS manner so that we can implement parallel processing in future. Demonstration of this method is done on two biological data sets and shown that we can find associated subgraphs for the biologically relevant set of vertices.