Author
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3 papers
Recent·Most cited
Geoffroy Dubourg-Felonneau, Daniel Wesego, Eyal Akiva, Ranjani Varadan
The paper introduces PiNUI, a PPI dataset designed for ML with improved representativeness, and shows it outperforms existing datasets in PPI tasks.
Geoffroy Dubourg-Felonneau, Arash Abbasi, Eyal Akiva, Lawrence Lee
The paper improves protein subcellular localization prediction by combining sequence-based language models and structure-based graph neural networks, achieving better performance with lower computational cost.
Geoffroy Dubourg-Felonneau, Shahab Shams, Eyal Akiva, Lawrence Lee
The paper introduces an unsupervised method using Transformer models, UMAP, and spectral clustering to organize protein sequences into biologically meaningful clusters.