Semantic Web Reasoning for Analyzing Gene Expression Profiles

  • Liviu Badea
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4187)


We argue that Semantic Web reasoning is an ideal tool for analyzing gene expression profiles and the resulting sets of differentially expressed genes produced by high-throughput microarray experiments, especially since this involves combining not only very large, but also semantically and structurally complex data and knowledge sources that are inherently distributed on the Web. In this paper, we describe an initial implementation of a full-fledged system for integrated reasoning about biological data and knowledge using Sematic Web reasoning technology and apply it to the analysis of a public pancreatic cancer dataset produced in the Pollack lab at Stanford.


Pancreatic Cancer Mapping Rule Query Planning Analyze Gene Expression Profile Semistructured Data 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Liviu Badea
    • 1
  1. 1.AI LabNational Institute for Research and Development in InformaticsBucharestRomania

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