Discovering gene-gene relations from sequential sentence patterns in biomedical literature

Jung Hsien Chiang, Hsiao Sheng Liu, Shih Yi Chao, Cheng Yu Chen

Research output: Contribution to journalArticlepeer-review

3 Citations (Scopus)


In this paper, we have developed a gene-gene relation browser (DiGG) that integrates sequential pattern-mining and information-extraction model to extract from biomedical literature knowledge on gene-gene interactions. DiGG combines efficient mining technique to enable the discovery of frequent gene-gene sequences even for very long sentences. Our approach aims to detect associated gene relations that are often discussed in documents. Integration of the related relations will lead to an individual gene relation network. Graphic presentation will be used to demonstrate the relationships between gene products. A salient feature of this approach is that it incrementally outputs new frequent gene relations in an online visualization fashion.

Original languageEnglish
Pages (from-to)1036-1041
Number of pages6
JournalExpert Systems With Applications
Issue number4
Publication statusPublished - 2007 Nov

All Science Journal Classification (ASJC) codes

  • Engineering(all)
  • Computer Science Applications
  • Artificial Intelligence


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