Gene Functional Annotation with Dynamic Hierarchical Classification Guided by Orthologs

  • Kazuhiro Seki
  • Yoshihiro Kino
  • Kuniaki Uehara
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5808)


This paper proposes an approach to automating Gene Ontology (GO) annotation in the framework of hierarchical classification that uses known, already annotated functions of the orthologs of a given gene. The proposed approach exploits such known functions as constraints and dynamically builds classifiers based on the training data available under the constraints. In addition, two unsupervised approaches are applied to complement the classification framework. The validity and effectiveness of the proposed approach are empirically demonstrated.


Gene ontology String matching Information retrieval 


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Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • Kazuhiro Seki
    • 1
  • Yoshihiro Kino
    • 1
  • Kuniaki Uehara
    • 1
  1. 1.Kobe UniversityKobeJapan

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