8 citations · 13 across the 6 of their papers we have counts for
6 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…
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…
CurateGPT: A flexible language-model assisted biocuration tool
Harry Caufield, Carlo Kroll, Shawn T O'Neil +10
Effective data-driven biomedical discovery requires data curation: a time-consuming process of finding, organizing, distilling, integrating, interpreting, annotating, and validatin…
MapperGPT: Large Language Models for Linking and Mapping Entities
Nicolas Matentzoglu, J. Harry Caufield, Harshad B. Hegde +6
Aligning terminological resources, including ontologies, controlled vocabularies, taxonomies, and value sets is a critical part of data integration in many domains such as healthca…
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…
KG-Hub -- Building and Exchanging Biological Knowledge Graphs
J Harry Caufield, Tim Putman, Kevin Schaper +23
Knowledge graphs (KGs) are a powerful approach for integrating heterogeneous data and making inferences in biology and many other domains, but a coherent solution for constructing,…