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Discovering Evolving Regions in Life Science Ontologies

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Data Integration in the Life Sciences (DILS 2010)

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Abstract

Ontologies are heavily used in life sciences and evolve continuously to incorporate new or changed insights. Often ontology changes affect only specific parts (regions) of ontologies making it valuable for ontology users and applications to know the heavily changed regions on the one hand and stable regions on the other hand. However, the size and complexity of life science ontologies renders manual approaches to localize changing or stable regions impossible. We therefore propose an approach to automatically discover evolving or stable ontology regions. We evaluate the approach by studying evolving regions in the Gene Ontology and the NCI Thesaurus.

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References

  1. Bodenreider, O., Stevens, R.: Bio-ontologies: current trends and future directions. Briefings in Bioinformatics 7(3), 256–274 (2006)

    Article  Google Scholar 

  2. Boutet, E., Lieberherr, D., Tognolli, M.: UniProtKB/Swiss-Prot. Methods in Molecular Biology 406, 89–112 (2007)

    Article  Google Scholar 

  3. Boyle, E.I., Weng, S., Gollub, J., et al.: GO:TermFinder - open source software for ac-cessing Gene Ontology information and finding significantly enriched Gene Ontology terms associated with a list of genes. Bioinformatics 20(18), 3710–3715 (2004)

    Article  Google Scholar 

  4. caBIG Strategic Planning Workspace: The Cancer Biomedical Informatics Grid (caBIG): infrastructure and applications for a worldwide research community. Studies Health Technology and Informatics 129, 330-334 (2007)

    Google Scholar 

  5. Euzenat, J., Shvaiko, P.: Ontology matching. Springer, Heidelberg (2007)

    MATH  Google Scholar 

  6. Floris, G., Manakanatas, D., Kondylakis, H., et al.: Ontology change: classification and survey. The Knowledge Engineering Review 23(2), 117–152 (2008)

    Google Scholar 

  7. The Gene Ontology Consortium: The Gene Ontology project in 2008. Nucleic Acids Research 36(Database issue), D440–D444 (2008)

    Google Scholar 

  8. Hartung, M., Kirsten, T., Gross, A., Rahm, E.: OnEX – Exploring changes in life science ontologies. BMC Bioinformatics 10, 250 (2009)

    Article  Google Scholar 

  9. Hartung, M., Kirsten, T., Rahm, E.: Analyzing the Evolution of Life Science Ontologies and Mappings. In: Bairoch, A., Cohen-Boulakia, S., Froidevaux, C. (eds.) DILS 2008. LNCS (LNBI), vol. 5109, pp. 11–27. Springer, Heidelberg (2008)

    Chapter  Google Scholar 

  10. Hubbard, T.J., Aken, B.L., Ayling, S., et al.: Ensembl 2009. Nucleic Acids Research 37(Database issue), D690–D697 (2009)

    Google Scholar 

  11. Kirsten, T., Hartung, M., Gross, A., Rahm, E.: Efficient Management of Biomedical Ontology Versions. In: Meersman, R., Herrero, P., Dillon, T.S. (eds.) OTM 2009 Workshops. LNCS, vol. 5872, pp. 574–583. Springer, Heidelberg (2009)

    Chapter  Google Scholar 

  12. Klein, M., Fensel, D.: Ontology versioning on the Semantic Web. In: Proceedings of the International Semantic Web Working Symposium (SWWS), pp. 75–91 (2001)

    Google Scholar 

  13. Komatsoulis, G.A., Warzel, D.B., Hartel, F.W., et al.: caCORE version 3: Implementation of a model driven, service-oriented architecture for semantic interoperability. Journal of Biomedical Informatics 41(1), 106–123 (2008)

    Article  Google Scholar 

  14. Lambrix, P., Tan, H., Jakoniene, V., Strömbäck, L.: Biological Ontologies. In: Semantic Web: Revolutionizing Knowledge Discovery in the Life Sciences, pp. 85–99 (2007)

    Google Scholar 

  15. Noy, N., Chugh, A., Liu, W., et al.: A Framework for Ontology Evolution in Collaborative Environments. In: Cruz, I., Decker, S., Allemang, D., Preist, C., Schwabe, D., Mika, P., Uschold, M., Aroyo, L.M. (eds.) ISWC 2006. LNCS, vol. 4273, pp. 544–558. Springer, Heidelberg (2006)

    Chapter  Google Scholar 

  16. Noy, N., Klein, M.: Ontology evolution: Not the same as schema evolution. Knowledge and Information Systems 6(4), 428–440 (2004)

    Article  Google Scholar 

  17. Noy, N., Musen, M.: Promptdiff: a fixed-point algorithm for comparing ontology versions. In: Proc. 18th Intl. Conference on Artificial Intelligence, pp. 744–750 (2002)

    Google Scholar 

  18. Noy, N., Musen, M.: Ontology versioning in an ontology management framework. IEEE Intelligent Systems 19(4), 6–13 (2004)

    Google Scholar 

  19. Papavassiliou, V., Flouris, G., Fundulaki, I., et al.: On Detecting High-Level Changes in RDF/S KBs. In: Bernstein, A., Karger, D.R., Heath, T., Feigenbaum, L., Maynard, D., Motta, E., Thirunarayan, K. (eds.) ISWC 2009. LNCS, vol. 5823, pp. 473–488. Springer, Heidelberg (2009)

    Chapter  Google Scholar 

  20. Plessers, P., De Troyer, O.: Ontology Change Detection Using a Version Log. In: Gil, Y., Motta, E., Benjamins, V.R., Musen, M.A. (eds.) ISWC 2005. LNCS, vol. 3729, pp. 578–592. Springer, Heidelberg (2005)

    Chapter  Google Scholar 

  21. Prüfer, K., Muetzel, B., Do, H.H., et al.: FUNC: a package for detecting significant associations between gene sets and ontological annotations. BMC Bioinformatics 8, 41 (2007)

    Article  Google Scholar 

  22. Sioutos, N., de Coronado, S., Haber, M.W., et al.: NCI Thesaurus: A semantic model integrating cancer-related clinical and molecular information. Journal of Biomedical Informatics 40(1), 30–43 (2007)

    Article  Google Scholar 

  23. Smith, B., Ashburner, M., Rosse, C., et al.: The OBO Foundry: coordinated evolution of ontologies to support biomedical data integration. Nature Biotechnology 25(11), 1251–1255 (2007)

    Article  Google Scholar 

  24. Stojanovic, L., Maedche, A., Motik, B., et al.: User-driven ontology evolution management. In: Gómez-Pérez, A., Benjamins, V.R. (eds.) EKAW 2002. LNCS (LNAI), vol. 2473, pp. 285–300. Springer, Heidelberg (2002)

    Chapter  Google Scholar 

  25. Stojanovic, L., Motik, B.: Ontology evolution within ontology editors. In: Proceedings of the International Workshop on Evaluation of Ontology-based Tools, pp. 53–62 (2002)

    Google Scholar 

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Hartung, M., Gross, A., Kirsten, T., Rahm, E. (2010). Discovering Evolving Regions in Life Science Ontologies. In: Lambrix, P., Kemp, G. (eds) Data Integration in the Life Sciences. DILS 2010. Lecture Notes in Computer Science(), vol 6254. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-15120-0_3

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  • DOI: https://doi.org/10.1007/978-3-642-15120-0_3

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-15119-4

  • Online ISBN: 978-3-642-15120-0

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