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An Ontology-Based Pattern Mining System for Extracting Information from Biological Texts

  • Muhammad Abulaish
  • Lipika Dey
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3642)

Abstract

Biological information embedded within the large repository of unstructured or semi-structured text documents can be extracted more efficiently through effective semantic analysis of the texts in collaboration with structured domain knowledge. The GENIA corpus houses tagged MEDLINE abstracts, manually annotated according to the GENIA ontology, for this purpose. However, manual tagging of all texts is impossible and special purpose storage and retrieval mechanisms are required to reduce information overload for users. In this paper we have proposed an ontology-based biological Information Extraction and Query Answering (BIEQA) system that has four components: an ontology-based tag analyzer for analyzing tagged texts to extract Biological and lexical patterns, an ontology-based tagger for tagging new texts, a knowledge base enhancer which enhances the ontology, and incorporates new knowledge in the form of biological entities and relationships into the knowledge base, and a query processor for handling user queries.

Keywords

Ontology-based text mining Biological information extraction Automatic tagging 

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References

  1. 1.
    Broekstra, J., Klein, M., Decker, S., Fensel, D., van Harmelen, F., Horrocks, I.: Enabling Knowledge Representation on the Web by Extending RDF Schema. In: Proceedings of the 10th Int. World Wide Web Conference, Hong Kong, pp. 467–478 (2001)Google Scholar
  2. 2.
    Collier, N., Nobata, C., Tsujii, J.: Extracting the Names of Genes and Gene Products with a Hidden Markov Model. In: Proceedings of the 18th Int. Conference on Computational Linguistics (COLING 2000), Saarbrucken Germany, pp. 201-207 (2000)Google Scholar
  3. 3.
    Craven, M., Kumlien, J.: Constructing Biological Knowledge Bases by Extracting Information from Text Sources. In: Proceedings of the 7th Int. Conference on Intelligent Systems for Molecular Biology (ISMB, Heidelburg Germany, pp. 77-86 (1999)Google Scholar
  4. 4.
    Friedman, C., Kra, P., Yu, H., Krauthammer, M., Rzhetsky, A.: GENIES: A Natural-Language Processing System for the Extraction of Molecular Pathways from Biomedical Texts. Bioinformatics 17, 74–82 (2001)Google Scholar
  5. 5.
    Fukuda, K., Tsunoda, T., Tamura, A., Takagi, T.: Toward Information Extraction: Identifying Protein Names from Biological papers. In: Pacific Symposium on Biocomputing, Maui Hawaii, pp. 707-718 (1998)Google Scholar
  6. 6.
    Gavrilis, D., Dermatas, E., Kokkinakis, G.: Automatic Extraction of Information from Molecular Biology Scientific Abstracts. In: Proceedings of the Int. Workshop on Speech and Computers (SPECOM 2003), Moscow, Russia (2003)Google Scholar
  7. 7.
    Kim, J.D., Ohta, T., Tateisi, Y., Tsujii, J.: GENIA corpus - A Semantically Annotated Corpus for Bio-Textmining. Bioinformatics 19(1), 180–182 (2003)CrossRefGoogle Scholar
  8. 8.
    Ono, T., Hishigaki, H., Tanigami, A., Takagi, T.: Automated Extraction of Information on Protein-Protein Interactions from the Biological Literature. Bioinformatics 17(2), 155–161 (2001)CrossRefGoogle Scholar
  9. 9.
    Rinaldi, F., Scheider, G., Andronis, C., Persidis, A., Konstani, O.: Mining Relations in the GENIA Corpus. In: Proceedings of the 2nd European Workshop on Data Mining and Text Mining for Bioinformatics, Pisa, Italy, pp. 61–68 (2004)Google Scholar
  10. 10.
    Stapley, B.J., Benoit, G.: Bibliometrics: Information Retrieval and Visualization from Co-occurrence of Gene Names in MedLine Abstracts. In: Proceedings of the Pacific Symposium on Biocomputing, Oahu Hawaii, pp. 529-540 (2000)Google Scholar
  11. 11.
    Su, K., Wu, M., Chang, J.: A Corpus-Based Approach to Automatic Compound Extraction. In: Proceedings of the 32nd Annual Meeting of the Association for Computational Linguistics (ACL 1994), Las Cruses New Maxico USA, pp. 242-247 (1994)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2005

Authors and Affiliations

  • Muhammad Abulaish
    • 1
  • Lipika Dey
    • 2
  1. 1.Department of MathematicsJamia Millia Islamia (A Central University)New DelhiIndia
  2. 2.Department of MathematicsIndian Institute of Technology, DelhiHauz Khas, New DelhiIndia

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