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Found 5 papers, 2 papers with code
Drug resistance revealed by in silico deep mutational scanning and mutation tracker
As COVID-19 enters its fifth year, it continues to pose a significant global health threat, with the constantly mutating SARS-CoV-2 virus challenging drug effectiveness.
Integration of persistent Laplacian and pre-trained transformer for protein solubility changes upon mutation
The Transformer, pretrained with hunderds of millions of protein sequences, embeds wild-type and mutant sequences, while persistent Laplacians track the topological invariant change and homotopic shape evolution induced by mutations in 3D protein structures, which are rendered from AlphaFold2.
Curvature-enhanced Graph Convolutional Network for Biomolecular Interaction Prediction
The results from the simulated data show that our CGCN model is superior to the traditional GCN models regardless of the positive-to-negativecurvature ratios, network densities, and network sizes (when larger than 500).
Persistent Dirac for molecular representation
A series of physical persistent attributes, which characterize the spectrum of the Dirac matrices across a filtration, are proposed and used as efficient molecular fingerprints.
Ollivier persistent Ricci curvature (OPRC) based molecular representation for drug design
Persistence and variation of Ollivier Ricci curvatures on these nested graphs are defined as Ollivier persistent Ricci curvature.
