Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely:  participated in the BioNLP 2013 shared tasks, addressing the GENIA (GE) and the Cancer Genetics (CG) event extraction tasks. Our event extraction is based on the system  recently proposed for mining relations and events involving genes or proteins in the biomedical literature using a novel, approximate subgraph matching-based approach. In addition to handling the GE task involving 13 event types uniformly related to molecular biology,  generalized our system to address the CG task targeting a challenging set of 40 event types related to cancer biology with various arguments involving 18 kinds of biological entities. Moreover,  attempted to integrate a distributional similarity model into our system to extend the graph matching scheme for more events. In addition,  evaluated the impact of using paths of all possible lengths among event participants as key contextual dependencies to extract potential events as compared to using only the shortest paths within the framework of our system.
['Haibin Liu', 'Karin Verspoor', 'Donald C. Comeau', 'Andrew MacKinlay', 'W. John Wilbur']
I am writing a research paper on a idea Generalizing an Approximate Subgraph Matching-based System to Extract Events in Molecular Biology and Cancer Genetics
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