Abstract
Researchers are faced with the challenge of integrating, on the basis of a common semantic web framework, the information on biological processes resulting from genomic and proteomic experimental studies. Researchers would like to integrate the biological processes’ roles in larger medical conditions, by taking account of the time dimension. This integration will support automated analysis and reasoning on the semantic web. We address these challenges by proposing the IGIPI framework, standing for “Integrating Gene Interactions and Protein Interactions”. IGIPI views different experimental studies as pieces of a puzzle that, if positioned properly, will contribute to a more complete representation of a biological process or medical condition over time. By representing the relative time points of events, this framework represents a biological process based on how it might be observed in an experiment over time. IGIPI involves integrating different ontologies and vocabularies, such as GO and UMLS/MeSH. We applied IGIPI to yeast and cancer examples. Availability: http://www.cse.yorku.ca/~billa/IGIPI/
Keywords
- Vascular Endothelial Growth Factor
- Biomedical Ontology
- Open Biomedical Ontology
- Biomedical Information
- Vascular Endothelial Growth Factor Binding
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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Andreopoulos, B., An, A., Huang, X., Labudde, D. (2008). Integration of Genomic, Proteomic and Biomedical Information on the Semantic Web. In: Song, IY., et al. Advances in Conceptual Modeling – Challenges and Opportunities. ER 2008. Lecture Notes in Computer Science, vol 5232. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-87991-6_5
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DOI: https://doi.org/10.1007/978-3-540-87991-6_5
Publisher Name: Springer, Berlin, Heidelberg
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