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.
1 code implementation • 5 Oct 2023 • Nicolas Matentzoglu, J. Harry Caufield, Harshad B. Hegde, Justin T. Reese, Sierra Moxon, HyeongSik Kim, Nomi L. Harris, Melissa A Haendel, Christopher J. Mungall
Here we present MapperGPT, an approach that uses LLMs to review and refine mapping relationships as a post-processing step, in concert with existing high-recall methods that are based on lexical and structural heuristics.
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.
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.
no code implementations • 5 Oct 2022 • Saurav Sengupta, Johanna Loomba, Suchetha Sharma, Donald E. Brown, Lorna Thorpe, Melissa A Haendel, Christopher G Chute, Stephanie Hong
Using our deep learning approach, we are able to predict if a patient is suffering from Long COVID from a temporally ordered list of diagnosis codes up to 45 days post the first COVID positive test or diagnosis for each patient, with an accuracy of 70. 48\%.