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Data Integration in the Life Sciences

Volume 5109 of the series Lecture Notes in Computer Science pp 153-160

Bio2RDF : A Semantic Web Atlas of Post Genomic Knowledge about Human and Mouse

  • François BelleauAffiliated withCentre de Recherche du CHUL, Université Laval, Département d’informatique et de génie logiciel, Université Laval, Bioinformatics Graduate Program, iCAPTURE Centre for Heart and Lung Research, University of British Columbia
  • , Nicole TourignyAffiliated withCentre de Recherche du CHUL, Université Laval, Département d’informatique et de génie logiciel, Université Laval, Bioinformatics Graduate Program, iCAPTURE Centre for Heart and Lung Research, University of British Columbia
  • , Benjamin GoodAffiliated withCentre de Recherche du CHUL, Université Laval, Département d’informatique et de génie logiciel, Université Laval, Bioinformatics Graduate Program, iCAPTURE Centre for Heart and Lung Research, University of British Columbia
  • , Jean MorissetteAffiliated withCentre de Recherche du CHUL, Université Laval, Département d’informatique et de génie logiciel, Université Laval, Bioinformatics Graduate Program, iCAPTURE Centre for Heart and Lung Research, University of British Columbia

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Abstract

The Bio2RDF project uses a data integration approach based on semantic web rules to answer a broad question: What is known about the mouse and human genomes? Using its rdfizing services, a semantic mashup of 65 million triples was built from 30 public bioinformatics data providers: GO, NCBI, UniProt, KEGG, PDB and many others. The average link-rank (ALR) of a node is 4.7 which means that a usual topic is connected to 4.7 other topics by direct or reverse links within the warehouse. A knowledge map of the graph and descriptive statistics about its content are presented. A downloadable version of the Bio2RDF Atlas graph in N3 format is available at http://bio2rdf.org/download.