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Exploring Evolution-aware & free protein language models as protein function predictors
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elttaes/Revisiting-PLMs
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data/
data/
ESMStructuralSplitDataset:
| Name | Description | URL |
|---|---|---|
| splits | train/valid splits | https://dl.fbaipublicfiles.com/fair-esm/structural-data/splits.tar.gz |
| pkl | pkl objects containing sequence, SSP labels, distance map, and 3d coordinates | https://dl.fbaipublicfiles.com/fair-esm/structural-data/pkl.tar.gz |
| msas | a3m files containing MSA for each domain | https://dl.fbaipublicfiles.com/fair-esm/structural-data/msas.tar.gz |
fromhttps://github.com/facebookresearch/esm
CAMEO(https://www.cameo3d.org/)
Tape(https://github.com/songlab-cal/tape)
Alphafold2 training data:
https://registry.opendata.aws/openfold/
from Openfold(https://github.com/aqlaboratory/openfold)
https://github.com/kalininalab/alphafold_non_docker
As a prerequisite, you must have PyTorch installed(https://pytorch.org/get-started/locally/).
pip install fair-esm # latest release, OR:
pip install git+https://github.com/facebookresearch/esm.git
@article{hu2022exploring,title={Exploring evolution-aware \&-free protein language models as protein function predictors},author={Hu, Mingyang and Yuan, Fajie and Yang, Kevin K and Ju, Fusong and Su, Jin and Wang, Hui and Yang, Fei and Ding, Qiuyang},journal={arXiv preprint arXiv:2206.06583},year={2022}}
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Exploring Evolution-aware & free protein language models as protein function predictors
Topics
benchmark pytorch contact-prediction stability multiple-sequence-alignment protein-annotation function-prediction protein-classification alphafold protein-language-model alphafold2 fitness-prediction zero-shot-prediction msa-construction msa-transformer esm1b remote-homology-detection metal-ion-binding