A Visual Cross-Database Comparison of Metabolic Networks

Bioinformatics research in general and the exploration of metabolic networks in particular rely on processing data from different sources. Visualization in this context supports the exploration process and helps to evaluate the data quality of the used sources. In this work, we extend our existing metabolic network visualization toolbox and hereby address the fundamental task of comparing metabolic networks from two major bioinformatics resources for the purpose of data validation and verification. This is done on different levels of granularity by providing an overview on retrieval rates of chemical compounds and reactions per pathway on the one hand, as well as giving a detailed insight into the differences in the biochemical reaction networks on the other. We reconstructed different subsets of the metabolism stored at the KEGG Pathway database and compare these networks against the complete metabolic network provided by the MetaCyc branch of the BioCyc database collection. Matches among the sets of chemical compounds and reactions are highlighted and propagated to higher levels of abstraction to infere pathway correspondence between the two resources.