Tobias Hamp

PrimateAI-3D outperforms AlphaMissense in real-world cohorts

The paper benchmarks PrimateAI-3D and AlphaMissense on real-world cohorts, finding PrimateAI-3D performs better in rare-disease and biobank settings.

The landscape of tolerated genetic variation in humans and primates

The paper uses primate genetic data to predict human variant pathogenicity with a deep learning classifier trained on 4.3 million common missense variants.

Rare penetrant mutations confer severe risk of common diseases

The paper identifies rare variant polygenic risk scores as more effective than common variant polygenic risk scores in identifying individuals with outlier phenotypes in common human diseases and complex traits.

ProfPPIdb: pairs of physical protein-protein interactions predicted for entire proteomes

The paper predicts novel protein-protein interactions for eight model organisms using sequence-based methods and provides these predictions through a web interface and downloadable data.