Locating basic bio-entities in genome-scale reconstructed metabolic networks

The numbers and use of Genome-Scale Reconstructed Metabolic Networks (GSRMN) have been increasing in recent years. Comparing and identifying matching metabolites, reactions, and compartments in GSRMNs can be difficult due to inconsistent naming in GSRMNs. In this paper, we propose metabolite & reaction identification techniques for GSRMNs (by matching metabolites & reactions to corresponding metabolites & reactions in different models). We employ a variety of techniques that include approximate string matching, similarity score functions and filtering techniques, all enhanced by a set of rules based on the underlying metabolic biochemistry. The proposed techniques are evaluated by an empirical study on four pairs of GSRMNs, and significant accuracy gains are achieved using the proposed metabolite & reaction identification techniques.