Database

Consistency, comprehensiveness, and compatibility of pathway databases

Donny Soh^3,1,2*, Difeng Dong¹, Yike Guo² and Limsoon Wong¹

• * Corresponding author: Donny Soh donnysoh@gmail.com

Author Affiliations

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

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BMC Bioinformatics 2010, 11:449 doi:10.1186/1471-2105-11-449

Published: 7 September 2010

Abstract

Background

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.

Description

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.

Conclusions

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.