113 citations · 141 across the 7 of their papers we have counts for
7 papers
LinkML: An Open Data Modeling Framework
Sierra A. T. Moxon, Harold Solbrig, Nomi L. Harris +33
Scientific research relies on well-structured, standardized data; however, much of it is stored in formats such as free-text lab notebooks, non-standardized spreadsheets, or data r…
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…
A Change Language for Ontologies and Knowledge Graphs
Harshad Hegde, Jennifer Vendetti, Damien Goutte-Gattat +9
Ontologies and knowledge graphs (KGs) are general-purpose computable representations of some domain, such as human anatomy, and are frequently a crucial part of modern information…
Automated Annotation of Scientific Texts for ML-based Keyphrase Extraction and Validation
Oluwamayowa O. Amusat, Harshad Hegde, Christopher J. Mungall +5
Advanced omics technologies and facilities generate a wealth of valuable data daily; however, the data often lacks the essential metadata required for researchers to find and searc…
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…
Structured prompt interrogation and recursive extraction of semantics (SPIRES): A method for populating knowledge bases using zero-shot learning
J. Harry Caufield, Harshad Hegde, Vincent Emonet +9
Creating knowledge bases and ontologies is a time consuming task that relies on a manual curation. AI/NLP approaches can assist expert curators in populating these knowledge bases,…
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,…