The pattern match query is user-defined, and thus modifiable. The query template can further be improved to allow modification of the queried length of the shunt pathway. The pattern matches were exported to a tabulated CSV file where several columns of information, e.g., the contents of each substructure path, the SMILES string of each molecule in the pattern, reaction information on each node, etc., were included for better visualization. Neo4j can also be used to compute various network statistics, including centrality measures for example: eigenvector and betweenness centrality, random-walk betweenness and node-degree metrics example: count of incoming or outgoing edges and node degree rank by generation, and the change in node degree by generation which may help assess when certain molecules become most influential in affecting network development.