emmijokinen / mgpfusion
mGPfusion is a Gaussian process based method for predicting stability changes upon single and multiple mutations of proteins that complements the available experimental data with large amounts of simulated data.
☆15Updated 6 years ago
Alternatives and similar repositories for mgpfusion:
Users that are interested in mgpfusion are comparing it to the libraries listed below
- ☆29Updated 4 years ago
- A surface-based deep learning approach for the prediction of ligand binding sites on proteins☆42Updated 2 years ago
- An unofficial re-implementation of AntiBERTy, an antibody-specific protein language model, in PyTorch.☆24Updated last year
- Guided Conditional Wasserstein GAN for De Novo Protein Design☆37Updated 4 years ago
- A DDG benchmark capture containing the benchmark dataset and benchmarked protocol captures.☆17Updated 9 years ago
- Rosetta FunFolDes – a general framework for the computational design of functional proteins.☆19Updated 6 years ago
- a fast and accurate physical energy function extended from EvoEF for protein sequence design☆29Updated 2 years ago
- This repo contains the collection of codes to find designer interfacial mutations☆17Updated last year
- ☆13Updated 7 years ago
- Spatiotemporal identification of druggable binding sites using deep learning☆22Updated 4 years ago
- Paratope Prediction using Deep Learning☆59Updated last year
- PDNET: A fully open-source framework for deep learning protein real-valued distances☆35Updated 3 years ago
- ☆19Updated last year
- test☆14Updated 4 years ago
- ☆34Updated 3 years ago
- Fork of matteofigliuzzi/bmDCA repository for Boltzmann-machine Direct Coupling Analysis (bmDCA).☆34Updated 4 years ago
- Protein-Ligand Interaction Fingerprints☆20Updated 4 years ago
- Use AlphaFold by Deep Mind in Batch Mode + Multiprocessing☆23Updated 3 years ago
- PCA and normal mode analysis of proteins☆17Updated 11 months ago
- Bayesian Active Learning for Optimization and Uncertainty Quantification with Applications to Protein Docking☆13Updated 4 years ago
- Docking benchmark 5 - cleaned and ready to use for HADDOCK☆13Updated 2 years ago
- ☆19Updated 2 years ago
- Enzyme datasets used to benchmark enzyme-substrate promiscuity models☆34Updated 3 years ago
- Pytorch implementation of BionoiNet, which is a deep learning-based software to classify ligand-binding sites.☆20Updated 3 years ago
- PyPEF – Pythonic Protein Engineering Framework☆24Updated 2 weeks ago
- ☆25Updated 3 years ago
- protein docking using a density-based descriptor for atoms charge and dynamics☆14Updated 2 years ago
- to assess structural quality of RNA using 3D CNN☆13Updated 6 years ago
- Protein-ligand binding sites prediction toolkits☆21Updated 6 years ago
- De novo design of small molecule binding sites into proteins☆12Updated 4 years ago