Chapter

Bioinformatics for Systems Biology

pp 385-399

GoPubMed: Exploring PubMed with Ontological Background Knowledge

  • Heiko DietzeAffiliated withTechnische Universität Dresden
  • , Dimitra AlexopoulouAffiliated withTechnische Universität Dresden
  • , Michael R. AlversAffiliated withTechnische Universität Dresden
  • , Liliana Barrio-AlversAffiliated withTechnische Universität Dresden
  • , Bill AndreopoulosAffiliated withTechnische Universität Dresden
  • , Andreas DomsAffiliated withTechnische Universität Dresden
  • , Jörg HakenbergAffiliated withTechnische Universität Dresden
  • , Jan MönnichAffiliated withTechnische Universität Dresden
  • , Conrad PlakeAffiliated withTechnische Universität Dresden
    • , Andreas ReischuckAffiliated withTechnische Universität Dresden
    • , Loïc RoyerAffiliated withTechnische Universität Dresden
    • , Thomas WächterAffiliated withTechnische Universität Dresden
    • , Matthias ZschunkeAffiliated withTechnische Universität Dresden
    • , Michael SchroederAffiliated withBiotec Email author 

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Abstract

With the ever increasing size of scientific literature, finding relevant documents and answering questions has become even more of a challenge. Recently, ontologies—hierarchical, controlled vocabularies—have been introduced to annotate genomic data. They can also improve the question and answering and the selection of relevant documents in the literature search. Search engines such as GoPubMed.org use ontological background knowledge to give an overview over large query results and to answer questions. We review the problems and solutions underlying these next-generation intelligent search engines and give examples of the power of this new search paradigm.

Keywords

PubMed Literature search Ontology Intelligent search