Abstract
In vivo experiments have had a great impact on the development of biomedicine, and as a result, a variety of biomedical data is produced and provided to researchers. Standardization and ontology design were carried out for the systematic management and effective sharing of these data. As results of their efforts, useful ontologies such as the Experimental Factor Ontology (EFO), Disease Ontology (DO), Gene Ontology (GO), Chemical Entities of Biological Interest (ChEBI) were developed. However, these ontologies are not enough to provide knowledge about the experiments to researchers conducting in vivo studies. Specifically, in the experimental design process, the generation of cancer causes considerable time and research costs. Researchers conducting animal experiments need animals with signs of carcinogenesis that fits their research interests. Therefore, our study is intended to provide experimental data about inducing cancer in animals. In order to provide this data, we collect experimental data about chemical substances that cause cancer. After that, we design an ontology based on these data and link it with the Disease Ontology. Our research focuses largely on two aspects. The first is to create a knowledge graph that inter-links with other biomedical linked data. The second is to provide practical knowledge to researchers conducting in vivo experiments. In conclusion, our research is provided in the form of a web service, which makes it easy to use the SPARQL endpoint and search service.
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Acknowledgements
This research was supported by the MSIT (Ministry of Science and ICT), Korea, under the ITRC (Information Technology Research Center) support program, (IITP-2017-0-00398) supervised by the IITP (Institute for Information & communications Technology Promotion) and the Institute for Information & communications Technology Promotion (IITP) grant funded by the Korea government (MSIP) (No.2013-0-00109, WiseKB: Big data based self-evolving knowledge base and reasoning platform). Authors want to thank Junhyuk Shin for the discussions they had.
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Yang, S., Joe, H., Yang, S., Kim, HG. (2020). CICO: Chemically Induced Carcinogenesis Ontology. In: Wang, X., Lisi, F., Xiao, G., Botoeva, E. (eds) Semantic Technology. JIST 2019. Lecture Notes in Computer Science(), vol 12032. Springer, Cham. https://doi.org/10.1007/978-3-030-41407-8_16
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DOI: https://doi.org/10.1007/978-3-030-41407-8_16
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