Implementation of ProteinBERT, a deep language model specifically designed for proteins. The official implementation of ProteinBERT is available at here.
$ pip install proteinbert-pytorch-reproductionfrom proteinbert_pytorch import ProteinBERT
vocab_size = 26
ann_size = 8943
seq_len = 512
bsz = 1
x_seq = torch.randint(0, vocab_size, (bsz, seq_len))
x_ann = torch.rand(bsz, ann_size)
model = ProteinBERT(vocab_size, ann_size)
x_seq_pred, x_ann_pred = model(x_seq, x_ann)@article{brandes2022proteinbert,
title={ProteinBERT: a universal deep-learning model of protein sequence and function},
author={Brandes, Nadav and Ofer, Dan and Peleg, Yam and Rappoport, Nadav and Linial, Michal},
journal={Bioinformatics},
volume={38},
number={8},
pages={2102--2110},
year={2022},
publisher={Oxford University Press}
}
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