3 citations · 4 across the 5 of their papers we have counts for
5 papers
Why we need all the organisms: an exploration of the Monarch knowledge graph to aid mechanism discovery
Katherina Cortes, Daniel Korn, Sarah Gehrke +12
Research done using model organisms has been fundamental to the biological understanding of human genes, diseases and phenotypes. Model organisms provide tractable systems for expe…
Standards in the Preparation of Biomedical Research Metadata: A Bridge2AI Perspective
Harry Caufield, Satrajit Ghosh, Sek Wong Kong +6
AI-readiness describes the degree to which data may be optimally and ethically used for subsequent AI and Machine Learning (AI/ML) methods, where those methods may involve some com…
Koza and Koza-Hub for born-interoperable knowledge graph generation using KGX
Daniel R Korn, Patrick Golden, Aaron Odell +10
Knowledge graph construction has become an essential domain for the future of biomedical research. But current approaches demand a high amount of redundant labor. These redundancie…
Improving Biomedical Knowledge Graph Quality: A Community Approach
Katherina G Cortes, Shilpa Sundar, Sarah Gehrke +13
Biomedical knowledge graphs (KGs) are widely used across research and translational settings, yet their design decisions and implementation are often opaque. Unlike ontologies that…
An evaluation of GPT models for phenotype concept recognition
Tudor Groza, Harry Caufield, Dylan Gration +5
Objective: Clinical deep phenotyping and phenotype annotation play a critical role in both the diagnosis of patients with rare disorders as well as in building computationally-trac…