=Paper=
{{Paper
|id=Vol-3805/ICBO-2022_paper_1944
|storemode=property
|title=Ontology Integration for Discovering Bioresources Contributing to Medical Science Research
|pdfUrl=https://ceur-ws.org/Vol-3805/ICBO-2022_paper_1944.pdf
|volume=Vol-3805
|authors=Tatsuya Kushida,Daiki Usuda,Toyoyuki Takada,Yuki Yamagata,Hiroshi Masuya
|dblpUrl=https://dblp.org/rec/conf/icbo/KushidaUTYM22
}}
==Ontology Integration for Discovering Bioresources Contributing to Medical Science Research==
https://ceur-ws.org/Vol-3805/ICBO-2022_paper_1944.pdf
Ontology Integration for Discovering Bioresources Contributing
to Medical Science Research
Tatsuya Kushida 1, Daiki Usuda 1, Toyoyuki Takada 1, Yuki Yamagata 2 and Hiroshi Masuya 1
1
RIKEN BioResource Research Center, Tsukuba, Japan
2
RIKEN Center for Biosystems Dynamics Research, Kobe, Japan
Abstract
We integrated the RIKEN bioresource RDF data with external public RDF data, such as OMA,
and disease ontologies, such as DOID and MONDO. Thus, we can discover the resources
relevant to diseases by performing a SPARQL query for the integrated RDF graph.
Keywords 1
Bioresource, Data Integration, Knowledge Graph, SPARQL
1. Introduction SPARQL query for the knowledge graph
(https://knowledge.brc.riken.jp/sparql).
RIKEN BioResource Research Center is one
of the largest comprehensive bioresource centers
that provide various kinds of bioresources such as
experimental animals (e.g., gene-modified mice),
cell materials (e.g., iPS cells), and DNA materials
(e.g., human cDNA clones). One of its missions is
to contribute to developing human health and
medical science research through the RIKEN
bioresources. We unitarily manage information
on the bioresources and provide it. In addition, we Figure 1: The bioresource RDF Graph integrated
develop the bioresource RDF data to promote data with external RDF data and ontologies
sharing and improve interoperability.
3. Reference
2. External data and ontology
integration and discovering [1] Altenhoff AM, Train CM, Gilbert KJ, et al.
OMA orthology in 2021: website overhaul,
bioresources relevant to diseases conserved isoforms, ancestral gene order and
more. Nucleic Acids Res.
We integrated the bioresource RDF data with 2021;49(D1):D373-D379.
OMA RDF data [1], DisGeNET RDF data, and doi:10.1093/nar/gkaa1007
disease ontologies, such as DOID, and MONDO
(Figure 1), to be able to simultaneously discover
mouse resources, cell materials, and DNA
materials relevant to diseases by performing a
ICBO 2022: International Conference on Biomedical Ontology,
September 25-28, 2022, Ann Arbor, MI, USA
EMAIL: tatsuya.kushida@riken.jp (A. 1); daiki.usuda@riken.jp
(A. 2); toyoyuki.takada@riken.jp (A. 3); yuki.yamagata@riken.jp
(A. 4); hiroshi.masuya@riken.jp (A. 5)
ORCID: 0000-0002-0784-4113 (A. 1); 0000-0001-6796-2085 (A.
3); 0000-0002-9673-1283 (A. 4); 0000-0002-3392-466X (A. 5)
© 2022 Copyright for this paper by its authors. Use permitted under Creative
Commons License Attribution 4.0 International (CC BY 4.0).
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