RNA-KG: An ontology-based knowledge graph for representing interactions involving RNA molecules

1 code implementation • 30 Nov 2023 • Emanuele Cavalleri, Alberto Cabri, Mauricio Soto-Gomez, Sara Bonfitto, Paolo Perlasca, Jessica Gliozzo, Tiffany J. Callahan, Justin Reese, Peter N Robinson, Elena Casiraghi, Giorgio Valentini, Marco Mesiti

The resource can be easily updated with new experimental data, and specific views of the overall KG can be extracted according to the bio-medical problem to be studied.

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