title: Matching metabolites and reactions in different metabolic networks.
abstract: Comparing and identifying matching metabolites, reactions, and compartments in genome-scale reconstructed metabolic networks can be difficult due to inconsistent naming in different networks. In this paper, we propose metabolite and reaction matching techniques for matching metabolites and reactions in a given metabolic network to metabolites and reactions in another metabolic network. We employ a variety of techniques that include approximate string matching, similarity score functions and multi-step 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 metabolic networks, and significant accuracy gains are achieved using the proposed metabolite and reaction identification techniques.
authors: Department of Electrical Engineering and Computer Science, Case Western Reserve University, United States. Electronic address: xinjian.qi@case.edu.
authors: Xinjian
authors: X
authors: Qi
authors: Department of Electrical Engineering and Computer Science, Case Western Reserve University, United States. Electronic address: meral@case.edu.
authors: Z Meral
authors: ZM
authors: Ozsoyoglu
authors: Department of Electrical Engineering and Computer Science, Case Western Reserve University, United States. Electronic address: tekin@case.edu.
authors: Gultekin
authors: G
authors: Ozsoyoglu
mesh_terms: D057225:Data Mining; D030541:Databases, Genetic; D016678:Genome; D006801:Humans; D053858:Metabolic Networks and Pathways / Q000235:genetics*; D008954:Models, Biological
keywords: Genome-scale reconstructed metabolic networks; Metabolic network; Reconstructed metabolic network