Pinned Repositories
binding_in_disorder
Prediction of Binding Residues in Disordered Regions Based on Protein Embeddings; TUM Master Praktikum Bioinformatics 2022 (Project #3) and Master's Thesis
DiffDock-PP
Implementation of DiffDock-PP: Rigid Protein-Protein Docking with Diffusion Models in PyTorch (ICLR 2023 - MLDD Workshop)
GeoDock
Flexible Protein-Protein Docking with a Multi-Track Iterative Transformer.
TMvisDB
TMvisDB provides per-residue transmembrane topology annotations for all proteins in AlphaFold DB (~ 200 million proteins, September '22) predicted as transmembrane proteins (~ 46 million).
VESPA
VESPA is a simple, yet powerful Single Amino Acid Variant (SAV) effect predictor based on embeddings of the Protein Language Model ProtT5.
VespaG
Expert-Guided Protein Language Models enable Accurate and Blazingly Fast Fitness Prediction
binding_in_disorder
Prediction of Binding Residues in Disordered Regions Based on Protein Embeddings; TUM Master Praktikum Bioinformatics 2022 (Project #3) and Master's Thesis
VespaG
Expert-Guided Protein Language Models enable Accurate and Blazingly Fast Fitness Prediction
TMvisDB
TMvisDB provides per-residue transmembrane topology annotations for all proteins in AlphaFold DB (~ 200 million proteins, September '22) predicted as transmembrane proteins (~ 46 million).
VESPA
VESPA is a simple, yet powerful Single Amino Acid Variant (SAV) effect predictor based on embeddings of the Protein Language Model ProtT5.
C-Marquet's Repositories
C-Marquet/TMvisDB
TMvisDB provides per-residue transmembrane topology annotations for all proteins in AlphaFold DB (~ 200 million proteins, September '22) predicted as transmembrane proteins (~ 46 million).
C-Marquet/binding_in_disorder
Prediction of Binding Residues in Disordered Regions Based on Protein Embeddings; TUM Master Praktikum Bioinformatics 2022 (Project #3) and Master's Thesis
C-Marquet/DiffDock-PP
Implementation of DiffDock-PP: Rigid Protein-Protein Docking with Diffusion Models in PyTorch (ICLR 2023 - MLDD Workshop)
C-Marquet/GeoDock
Flexible Protein-Protein Docking with a Multi-Track Iterative Transformer.
C-Marquet/VESPA
VESPA is a simple, yet powerful Single Amino Acid Variant (SAV) effect predictor based on embeddings of the Protein Language Model ProtT5.
C-Marquet/VespaG
Expert-Guided Protein Language Models enable Accurate and Blazingly Fast Fitness Prediction