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This article is part of the supplement: APBioNet – Fifth International Conference on Bioinformatics (InCoB2006)

Open Access Highly Accessed Proceedings

An evaluation of human protein-protein interaction data in the public domain

Suresh Mathivanan123, Balamurugan Periaswamy123, TKB Gandhi12, Kumaran Kandasamy13, Shubha Suresh12, Riaz Mohmood3, YL Ramachandra3 and Akhilesh Pandey2*

Author Affiliations

1 Institute of Bioinformatics, International Technology Park, Bangalore, India

2 McKusick-Nathans Institute of Genetic Medicine and the Departments of Biological Chemistry, Pathology and Oncology, Johns Hopkins University, Baltimore, MD 21205, USA

3 Department of Biotechnology, Kuvempu University, Shankaraghatta, Karnataka, India

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BMC Bioinformatics 2006, 7(Suppl 5):S19  doi:10.1186/1471-2105-7-S5-S19

Published: 18 December 2006

Abstract

Background

Protein-protein interaction (PPI) databases have become a major resource for investigating biological networks and pathways in cells. A number of publicly available repositories for human PPIs are currently available. Each of these databases has their own unique features with a large variation in the type and depth of their annotations.

Results

We analyzed the major publicly available primary databases that contain literature curated PPI information for human proteins. This included BIND, DIP, HPRD, IntAct, MINT, MIPS, PDZBase and Reactome databases. The number of binary non-redundant human PPIs ranged from 101 in PDZBase and 346 in MIPS to 11,367 in MINT and 36,617 in HPRD. The number of genes annotated with at least one interactor was 9,427 in HPRD, 4,975 in MINT, 4,614 in IntAct, 3,887 in BIND and <1,000 in the remaining databases. The number of literature citations for the PPIs included in the databases was 43,634 in HPRD, 11,480 in MINT, 10,331 in IntAct, 8,020 in BIND and <2,100 in the remaining databases.

Conclusion

Given the importance of PPIs, we suggest that submission of PPIs to repositories be made mandatory by scientific journals at the time of manuscript submission as this will minimize annotation errors, promote standardization and help keep the information up to date. We hope that our analysis will help guide biomedical scientists in selecting the most appropriate database for their needs especially in light of the dramatic differences in their content.