title: When the Web meets the cell: using personalized PageRank for analyzing protein interaction networks.
abstract: BACKGROUND
  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.
  
  
  BACKGROUND
  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.
authors.affiliation: Protein Information Technology Group, Eötvös University, Pázmány Péter sétány 1/C and Uratim Ltd., InfoPark D, H-1117 Budapest, Hungary.
authors.forename: Gábor
authors.initials: G
authors.lastname: Iván
authors.forename: Vince
authors.initials: V
authors.lastname: Grolmusz
mesh_terms: D000465:Algorithms; D030562:Databases, Protein; D006801:Humans; D020407:Internet; D060066:Protein Interaction Maps; D040901:Proteomics / Q000379:methods*