Dynamic Retrieval Augmented Generation of Ontologies using Artificial Intelligence (DRAGON-AI)

no code implementations • 18 Dec 2023 • Sabrina Toro, Anna V Anagnostopoulos, Sue Bello, Kai Blumberg, Rhiannon Cameron, Leigh Carmody, Alexander D Diehl, Damion Dooley, William Duncan, Petra Fey, Pascale Gaudet, Nomi L Harris, Marcin Joachimiak, Leila Kiani, Tiago Lubiana, Monica C Munoz-Torres, Shawn O'Neil, David Osumi-Sutherland, Aleix Puig, Justin P Reese, Leonore Reiser, Sofia Robb, Troy Ruemping, James Seager, Eric Sid, Ray Stefancsik, Magalie Weber, Valerie Wood, Melissa A Haendel, Christopher J Mungall

However, our results also underscore the importance of having expert curators and ontology editors drive the ontology generation process.

Retrieval

An evaluation of GPT models for phenotype concept recognition

no code implementations • 29 Sep 2023 • Tudor Groza, Harry Caufield, Dylan Gration, Gareth Baynam, Melissa A Haendel, Peter N Robinson, Christopher J Mungall, Justin T Reese

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-tractable knowledge in the rare disorders field.

Few-Shot Learning Specificity

KG-Hub -- Building and Exchanging Biological Knowledge Graphs

no code implementations • 31 Jan 2023 • J Harry Caufield, Tim Putman, Kevin Schaper, Deepak R Unni, Harshad Hegde, Tiffany J Callahan, Luca Cappelletti, Sierra AT Moxon, Vida Ravanmehr, Seth Carbon, Lauren E Chan, Katherina Cortes, Kent A Shefchek, Glass Elsarboukh, James P Balhoff, Tommaso Fontana, Nicolas Matentzoglu, Richard M Bruskiewich, Anne E Thessen, Nomi L Harris, Monica C Munoz-Torres, Melissa A Haendel, Peter N Robinson, Marcin P Joachimiak, Christopher J Mungall, Justin T Reese

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, exchanging, and facilitating the downstream use of knowledge graphs is lacking.

Knowledge Graphs Link Prediction +1

Recommendations for extending the GFF3 specification for improved interoperability of genomic data

no code implementations • 15 Feb 2022 • Surya Saha, Scott Cain, Ethalinda K. S. Cannon, Nathan Dunn, Andrew Farmer, Zhi-Liang Hu, Gareth Maslen, Sierra Moxon, Christopher J Mungall, Rex Nelson, Monica F. Poelchau

The GFF3 format is a common, flexible tab-delimited format representing the structure and function of genes or other mapped features (https://github. com/The-Sequence-Ontology/Specifications/blob/master/gff3. md).