GPS-Prot: A web-based visualization platform for integrating host-pathogen interaction data
- Equal contributors
1 Department of Cellular and Molecular Pharmacology, University of California San Francisco, 1700 4th Street, San Francisco, 94158 USA
2 Department of Biochemistry and Biophysics, University of California San Francisco, 600 16th Street, San Francisco, 94158 USA
3 Department of Pharmaceutical Chemistry, University of California San Francisco, 600 16th Street, San Francisco, 94158 USA
4 Sanford-Burnham Medical Research Institute, 10901 North Torrey Pines Road, La Jolla, 92037 USA
5 Immunology Group, International Centre for Genetic Engineering and Biotechnology, Aruna Asaf Marg, New Delhi 110 067, India
6 TouchGraph LLC, 306 W. 92nd Street #3F, New York, 10025 USA
BMC Bioinformatics 2011, 12:298 doi:10.1186/1471-2105-12-298Published: 22 July 2011
The increasing availability of HIV-host interaction datasets, including both physical and genetic interactions, has created a need for software tools to integrate and visualize the data. Because these host-pathogen interactions are extensive and interactions between human proteins are found within many different databases, it is difficult to generate integrated HIV-human interaction networks.
We have developed a web-based platform, termed GPS-Prot http://www.gpsprot.org webcite, that allows for facile integration of different HIV interaction data types as well as inclusion of interactions between human proteins derived from publicly-available databases, including MINT, BioGRID and HPRD. The software has the ability to group proteins into functional modules or protein complexes, generating more intuitive network representations and also allows for the uploading of user-generated data.
GPS-Prot is a software tool that allows users to easily create comprehensive and integrated HIV-host networks. A major advantage of this platform compared to other visualization tools is its web-based format, which requires no software installation or data downloads. GPS-Prot allows novice users to quickly generate networks that combine both genetic and protein-protein interactions between HIV and its human host into a single representation. Ultimately, the platform is extendable to other host-pathogen systems.