{"database":"biostudies-literature","file_versions":[],"scores":null,"additional":{"omics_type":["Unknown"],"volume":["15(1)"],"submitter":["Toro S"],"pubmed_abstract":["<h4>Background</h4>Ontologies are fundamental components of informatics infrastructure in domains such as biomedical, environmental, and food sciences, representing consensus knowledge in an accurate and computable form. However, their construction and maintenance demand substantial resources and necessitate substantial collaboration between domain experts, curators, and ontology experts. We present Dynamic Retrieval Augmented Generation of Ontologies using AI (DRAGON-AI), an ontology generation method employing Large Language Models (LLMs) and Retrieval Augmented Generation (RAG). DRAGON-AI can generate textual and logical ontology components, drawing from existing knowledge in multiple ontologies and unstructured text sources.<h4>Results</h4>We assessed performance of DRAGON-AI on de nov"],"journal":["Journal of biomedical semantics"],"pagination":["19"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/S-EPMC11484368"],"repository":["biostudies-literature"],"pubmed_title":["Dynamic Retrieval Augmented Generation of Ontologies using Artificial Intelligence (DRAGON-AI)."],"pmcid":["PMC11484368"],"pubmed_authors":["Wood V","Duncan WD","Robb SM","Lubiana T","O'Neil S","Puig-Barbe A","Sid E","Seager J","Dooley DM","Carmody L","Blumberg K","Bello SM","Diehl AD","Fey P","Kiani L","Weber M","Toro S","Harris NL","Joachimiak MP","Mungall CJ","Munoz-Torres MC","Gaudet P","Reiser L","Reese JT","Haendel MA","Ruemping T","Cameron R","Osumi-Sutherland D","Anagnostopoulos AV","Stefancsik R"],"additional_accession":[]},"is_claimable":false,"name":"Dynamic Retrieval Augmented Generation of Ontologies using Artificial Intelligence (DRAGON-AI).","description":"<h4>Background</h4>Ontologies are fundamental components of informatics infrastructure in domains such as biomedical, environmental, and food sciences, representing consensus knowledge in an accurate and computable form. However, their construction and maintenance demand substantial resources and necessitate substantial collaboration between domain experts, curators, and ontology experts. We present Dynamic Retrieval Augmented Generation of Ontologies using AI (DRAGON-AI), an ontology generation method employing Large Language Models (LLMs) and Retrieval Augmented Generation (RAG). DRAGON-AI can generate textual and logical ontology components, drawing from existing knowledge in multiple ontologies and unstructured text sources.<h4>Results</h4>We assessed performance of DRAGON-AI on de nov","dates":{"release":"2024-01-01T00:00:00Z","publication":"2024 Oct","modification":"2025-04-04T20:55:04.107Z","creation":"2025-04-04T20:55:04.107Z"},"accession":"S-EPMC11484368","cross_references":{"pubmed":["39415214"],"doi":["10.1186/s13326-024-00320-3"]}}