Consensus and conflict cards for metabolic pathway databases

• Published in: BMC systems biology Vol. 7; no. 1; p. 50
• Main Authors: Stobbe, Miranda D, Swertz, Morris A, Thiele, Ines, Rengaw, Trebor, van Kampen, Antoine HC, Moerland, Perry D
• Format: Journal Article
• Language: English
• Published: London BioMed Central 26.06.2013; BioMed Central Ltd
• Subjects: Algorithms; Analysis; Bioinformatics; Biology; Biomedical and Life Sciences; Case studies; Cell metabolism; Cellular and Medical Topics; Colleges & universities; Community involvement; Computational Biology/Bioinformatics; Conflict (Psychology); Consensus; Data Mining - methods; Databases, Genetic; Encyclopedias; Genealogical libraries; Genomes; Humans; Life Sciences; Metabolic Networks and Pathways - genetics; Metabolites; Methods; Phenotype; Physiological; Research Article; Simulation and Modeling; software and technology; Systems Biology; Human; Pathway database; Metabolic network; Community support; Consensus
• ISSN: 1752-0509; 1752-0509
• DOI: 10.1186/1752-0509-7-50

Background The metabolic network of H. sapiens and many other organisms is described in multiple pathway databases. The level of agreement between these descriptions, however, has proven to be low. We can use these different descriptions to our advantage by identifying conflicting information and combining their knowledge into a single, more accurate, and more complete description. This task is, however, far from trivial. Results We introduce the concept of Consensus and Conflict Cards (C 2 Cards) to provide concise overviews of what the databases do or do not agree on. Each card is centered at a single gene, EC number or reaction. These three complementary perspectives make it possible to distinguish disagreements on the underlying biology of a metabolic process from differences that can be explained by different decisions on how and in what detail to represent knowledge. As a proof-of-concept, we implemented C 2 Cards Human , as a web application http://www.molgenis.org/c2cards , covering five human pathway databases. Conclusions C 2 Cards can contribute to ongoing reconciliation efforts by simplifying the identification of consensus and conflicts between pathway databases and lowering the threshold for experts to contribute. Several case studies illustrate the potential of the C 2 Cards in identifying disagreements on the underlying biology of a metabolic process. The overviews may also point out controversial biological knowledge that should be subject of further research. Finally, the examples provided emphasize the importance of manual curation and the need for a broad community involvement.