When the Web meets the cell: using personalized PageRank for analyzing protein interaction networks
- Gábor Iván1,2 and
- Vince Grolmusz1,2,*
- 1Protein Information Technology Group, Eötvös University, Pázmány Péter sétány 1/C and 2Uratim Ltd., InfoPark D, H-1117 Budapest, Hungary
- * To whom correspondence should be addressed.
- Received April 22, 2010.
- Revision received October 25, 2010.
- Accepted December 7, 2010.
Abstract
Motivation: Enormous and constantly increasing quantity of biological information is represented in metabolic and in protein interaction network databases. Most of these data are freely accessible through large public depositories. The robust analysis of these resources needs novel technologies, being developed today.
Results: Here we demonstrate a technique, originating from the PageRank computation for the World Wide Web, for analyzing large interaction networks. The method is fast, scalable and robust, and its capabilities are demonstrated on metabolic network data of the tuberculosis bacterium and the proteomics analysis of the blood of melanoma patients.
Availability: The Perl script for computing the personalized PageRank in protein networks is available for non-profit research applications (together with sample input files) at the address: http://uratim.com/pp.zip
Contact: grolmusz{at}cs.elte.hu.
Supplementary information: Supplementary data are available at Bioinformatics online.
- © The Author 2010. Published by Oxford University Press. All rights reserved. For Permissions, please email: [email protected]
