ConQuR-Bio: Consensus Ranking with Query Reformulation for Biological Data

  • Bryan Brancotte
  • Bastien Rance
  • Alain Denise
  • Sarah Cohen-Boulakia
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8574)


This paper introduces ConQuR-Bio which aims at assisting scientists when they query public biological databases. Various reformulations of the user query are generated using medical terminologies. Such alternative reformulations are then used to rank the query results using a new consensus ranking strategy. The originality of our approach thus lies in using consensus ranking techniques within the context of query reformulation. The ConQuR-Bio system is able to query the EntrezGene NCBI database. Our experiments demonstrate the benefit of using ConQuR-Bio compared to what is currently provided to users. ConQuR-Bio is available to the bioinformatics community at .


Lynch Syndrome MeSH Term Median Ranking Query Reformulation Consensus Ranking 
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 International Publishing Switzerland 2014

Authors and Affiliations

  • Bryan Brancotte
    • 1
    • 2
  • Bastien Rance
    • 4
    • 5
  • Alain Denise
    • 1
    • 2
    • 3
  • Sarah Cohen-Boulakia
    • 1
    • 2
  1. 1.Laboratoire de Recherche en Informatique (LRI), CNRS UMR 8623Université Paris-SudOrsay CedexFrance
  2. 2.AMIB Group, INRIA Saclay Ile-de-FranceFrance
  3. 3.Institut de Génétique et de Microbiologie (IGM), CNRS UMR 8621Université Paris-SudFrance
  4. 4.Biomedical Informatics and Public Health DepartmentUniversity Hospital Georges Pompidou, AP-HPParisFrance
  5. 5.INSERM Centre de Recherche des Cordeliers, team 22: Information Sciences to support Personalized MedicineUniversité Paris Descartes, Sorbonne Paris Cité, Faculté de médecineParisFrance

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