Mondo: A Unified Disease Resource Connecting Clinical and Translational Research
This webinar presents insights on the systematic curation of disease concept mappings in Mondo which is a unified disease resource connecting clinical and translational research.
Numerous sources for disease definitions and data models currently exist, which include HPO, OMIM, SNOMED CT, ICD, PhenoDB, MedDRA, MedGen, ORDO, DO, GARD, etc; however, these sources partially overlap and sometimes conflict, making it difficult to know definitively how they relate to each other. This has resulted in a proliferation of mappings between disease entries in different resources. However, mappings are problematic: collectively, they are expensive to create and maintain.
Most importantly, the mappings lack completeness, accuracy, and precision; as a result, mapping calls are often inconsistent between resources. The UMLS provides intermediate concepts through which other resources can be mapped, but these mappings suffer from the same challenges: they are not guaranteed to be one-to-one, especially in areas with evolving disease concepts such as rare disease.
In order to address the lack of a unified disease terminology that provides precise equivalences between disease concepts, we created Mondo, which provides a logic-based structure for unifying multiple disease resources. Mondo utilizes human curation assisted by a combination of logical, probabilistic, and lexical methods to assist in curation and hone curation on difficult areas, together with fostering a broader community of disease resources committed to working together.
Chris Mungall, Department Head, Molecular Ecosystems Biology, Berkeley Lab
Chris Mungall leads a group working on the application of computational techniques to life sciences problems of relevance to the health of humans and the planetary ecosystem. His main interest is the application of artificial intelligence, knowledge-based methods, and bio-curation to advance our understanding of the interconnected role of genes and genetic mechanisms in key biological processes.
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