Consistency, comprehensiveness, and compatibility of pathway databases
1 School of Computing, National University of Singapore, Building COM1, 117417 Singapore
2 Department of Computing. Imperial College London. 180 Queen's Gate. London SW7 2BZ, UK
3 Institute for Infocomm Research, 1 Fusionopolis Way, 138632 Singapore
BMC Bioinformatics 2010, 11:449 doi:10.1186/1471-2105-11-449Published: 7 September 2010
It is necessary to analyze microarray experiments together with biological information to make better biological inferences. We investigate the adequacy of current biological databases to address this need.
Our results show a low level of consistency, comprehensiveness and compatibility among three popular pathway databases (KEGG, Ingenuity and Wikipathways). The level of consistency for genes in similar pathways across databases ranges from 0% to 88%. The corresponding level of consistency for interacting genes pairs is 0%-61%. These three original sources can be assumed to be reliable in the sense that the interacting gene pairs reported in them are correct because they are curated. However, the lack of concordance between these databases suggests each source has missed out many genes and interacting gene pairs.
Researchers will hence find it challenging to obtain consistent pathway information out of these diverse data sources. It is therefore critical to enable them to access these sources via a consistent, comprehensive and unified pathway API. We accumulated sufficient data to create such an aggregated resource with the convenience of an API to access its information. This unified resource can be accessed at http://www.pathwayapi.com webcite.