Disease ontologies for knowledge graphs.

Journal: BMC bioinformatics
Published Date:

Abstract

BACKGROUND: Data integration to build a biomedical knowledge graph is a challenging task. There are multiple disease ontologies used in data sources and publications, each having its hierarchy. A common task is to map between ontologies, find disease clusters and finally build a representation of the chosen disease area. There is a shortage of published resources and tools to facilitate interactive, efficient and flexible cross-referencing and analysis of multiple disease ontologies commonly found in data sources and research.

Authors

  • Natalja Kurbatova
    Data Infrastructure & Tools, Data Science & Artificial Intelligence, R&D, AstraZeneca, Cambridge, UK. natalie.kurbatova@astrazeneca.com.
  • Rowan Swiers
    Quantitative Biology, BioPharmaceuticals R&D, AstraZeneca, Cambridge, UK.