203 citations · 389 across the 9 of their papers we have counts for
3 papers · 1 filter
Protein sequence-to-structure learning: Is this the end(-to-end revolution)?
Elodie Laine, Stephan Eismann, Arne Elofsson +1
The potential of deep learning has been recognized in the protein structure prediction community for some time, and became indisputable after CASP13. In CASP14, deep learning has b…
Learning from Protein Structure with Geometric Vector Perceptrons
Bowen Jing, Stephan Eismann, Patricia Suriana +2
Learning on 3D structures of large biomolecules is emerging as a distinct area in machine learning, but there has yet to emerge a unifying network architecture that simultaneously…
Hierarchical, rotation-equivariant neural networks to select structural models of protein complexes
Stephan Eismann, Raphael J. L. Townshend, Nathaniel Thomas +3
Predicting the structure of multi-protein complexes is a grand challenge in biochemistry, with major implications for basic science and drug discovery. Computational structure pred…