Gene ontology classification of biomedical literatures using context association

  • Authors:

  • Ki Chan;Wai Lam

  • Affiliations:

  • Department of Systems Engineering and Engineering Management, The Chinese University of Hong Kong, Shatin, Hong Kong;Department of Systems Engineering and Engineering Management, The Chinese University of Hong Kong, Shatin, Hong Kong

  • Venue:
  • AIRS'05 Proceedings of the Second Asia conference on Asia Information Retrieval Technology
  • Year:
  • 2005

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Abstract

The functional annotation of gene products from biomedical literatures has become a pressing issue due to the huge human efforts involved and the evolving biomedical knowledge. In this paper, we propose an approach for facilitating this functional annotation to the Gene Ontology by focusing on a subtask of annotation, that is, to determine which of the Gene Ontology a literature is associated with. This subtask can be formulated as a document classification problem. A feature engineering approach using context association conveyed in the biomedical literatures, in particular, utilizing the proximity relationship between target gene(s) and term features is proposed. Our approach achieves an F-score of 60.24%, which outperforms the submission runs of TREC Genomics 2004 annotation hierarchy subtask. We show that incorporation of context association can enhance the performance of the annotation hierarchy classification problem.