deep-vaccine
Predict multi-epitope vaccine subunit candidates using NLP.
Science Score: 18.0%
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✓CITATION.cff file
Found CITATION.cff file -
○codemeta.json file
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○Scientific vocabulary similarity
Low similarity (5.1%) to scientific vocabulary
Keywords
Repository
Predict multi-epitope vaccine subunit candidates using NLP.
Basic Info
- Host: GitHub
- Owner: yuanx749
- License: mit
- Language: TeX
- Default Branch: main
- Homepage: https://yuanx749.github.io/deep-vaccine/
- Size: 4.5 MB
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Metadata Files
README.md
deep-vaccine
Predict multi-epitope vaccine subunit candidates using NLP.
Data
Immune Epitope Database (IEDB)
Construct datasets with data/preprocess.py (notebook format used by mainstream editors).
Environment
Usage
To train, python train.py, or use LSTM.ipynb on Colab. Models are saved in ./runs.
Predict a list of sequences using a model saved at path_to_model as follows:
```python
from api import Predictor
seqs = """ PVAGAAIAAPVAGQQGPQRR IAADFVEDQEVCKNYTGTVVGFASMVA ADGAYRFLSGTAAVLAAAETAEAKAAAAAE GDNLKGIVVIKDRNIGVLGENGSHMPDRCN """.split()
predictor = Predictor(pathtomodel) predictor.predict_proba(seqs) ```
An application on the spike protein of SARS-CoV-2 is in example.py.
Misc.
- Models: (CNN+) LSTM/GRU, Transformer
- Different tokenizers and pooling
- Visualize models, data, training:
tensorboard --logdir=runs
If you find this helpful, please consider citing (bib).
Owner
- Name: Xiao Yuan
- Login: yuanx749
- Kind: user
- Repositories: 30
- Profile: https://github.com/yuanx749
Citation (CITATION.bib)
@INPROCEEDINGS{9635304,
author={Yuan, Xiao and Bibl, Daniel and Khan, Kahlil and Sun, Lei},
booktitle={2021 IEEE 21st International Conference on Bioinformatics and Bioengineering (BIBE)},
title={Predicting Multi-Epitope Vaccine Candidates Using Natural Language Processing and Deep Learning},
year={2021},
doi={10.1109/BIBE52308.2021.9635304}
}
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