[1Win4] Poster session 1

[1Win4-17] Construction of a Viral Disease Knowledge Graph and Exploration of Disease Model Animals

〇Tatsuya Kushida¹, Daiki Usuda¹, Yuki Yamagata¹, Toyoyuki Takada¹, Norio Kobayashi¹, Hiroshi Masuya¹ (1. RIKEN)

Keywords:Viral disease, Knowledge graph, Data integration, Symptom, Phenotype

We constructed a knowledge graph of viral diseases that covers 44 types of human viral diseases, including COVID-19. This graph integrates information about the infection cycle (e.g., virion attachment to and entry into host cells, viral genome replication, and release from host cells), associated biological processes, and malfunctioning processes such as host symptoms and phenotypes. The knowledge graph was manually curated from literature and databases, providing detailed information, including 122 human proteins involved in the COVID-19 infection process. By integrating this graph with the bioresource knowledge graph maintained by RIKEN BRC, as well as various ontologies related to proteins, diseases, symptoms, and phenotypes, we identified 63 genetically modified mouse models and 1,443 DNA clones that are potentially valuable for COVID-19 research. Experimental researchers can efficiently explore these knowledge graphs through the newly developed Bioresource Advanced Search system (https://web.brc.riken.jp/).