amyxlu / CPCProt
Parameter-efficient embeddings for proteins, pretrained using a contrastive loss.
☆29Updated 4 years ago
Alternatives and similar repositories for CPCProt:
Users that are interested in CPCProt are comparing it to the libraries listed below
- An unofficial re-implementation of AntiBERTy, an antibody-specific protein language model, in PyTorch.☆24Updated last year
- Code associated with "Biophysical prediction of protein-peptide interactions and signaling networks using machine learning."☆71Updated last year
- pyFoldX: python bindings for FoldX.☆44Updated 3 years ago
- Predict the structure of immune receptor proteins☆48Updated 5 months ago
- Prediction of binding residues for metal ions, nucleic acids, and small molecules.☆32Updated 4 months ago
- Paratope Prediction using Deep Learning☆59Updated last year
- PyTorch implementation of Parapred (Liberis et al., 2018) with Paratyping (Richardson et al., 2021)☆20Updated last year
- ☆19Updated 4 years ago
- Public repository describing training and testing of AntiBERTa.☆58Updated 2 years ago
- HoTS: Sequence-based prediction of binding regions and drug-target interactions.☆26Updated 2 years ago
- GraphSite: protein-DNA binding site prediction using graph transformer and predicted protein structures☆59Updated 8 months ago
- A complete, open-source, end-to-end re-implementation of the Church Lab's low-N eUniRep in silico protein engineering pipeline presented …☆27Updated 4 years ago
- PaccMann models for protein language modeling☆42Updated 3 years ago
- Multi-Channel Deep Chemogenomic Modeling of Receptor-Ligand Binding Affinity Prediction for Drug Discovery☆27Updated 3 years ago
- Python package for peptide sequence generation, peptide descriptor calculation and sequence analysis.☆58Updated last month
- Protein language model trained on coding DNA☆46Updated 6 months ago
- PDNET: A fully open-source framework for deep learning protein real-valued distances☆35Updated 3 years ago
- PLM based active learning model for protein engineering☆78Updated 8 months ago
- Preforms De novo protein design using machine learning and PyRosetta to generate a novel protein structure☆52Updated last month
- Inference code for PoET: A generative model of protein families as sequences-of-sequences☆71Updated last year
- Generating and scoring novel enzyme sequences with a variety of models and metrics☆69Updated 3 months ago
- ☆46Updated 6 months ago
- A structure-based, alignment-free embedding approach for proteins. Can be used as input to machine learning algorithms.☆37Updated last year
- Machine learning models for antibody sequences in PyTorch☆39Updated 3 years ago
- ☆34Updated 3 years ago
- Code for our paper "Protein sequence design with a learned potential"☆79Updated last year
- Learning with uncertainty for biological discovery and design☆34Updated 2 years ago
- Python package to atom map, correct and suggest enzymatic reactions☆37Updated last year
- The code used to generate the results from Parkinson / Hard et al. 2022☆17Updated 5 months ago
- ☆45Updated last year