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Qin Wang a848779dcf | 3 years ago | |
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DataLoader | 4 years ago | |
a3ms | 4 years ago | |
bert_pssms | 4 years ago | |
configs | 4 years ago | |
enhanced_pssms | 4 years ago | |
img | 4 years ago | |
labels | 4 years ago | |
low_pssms | 4 years ago | |
models | 4 years ago | |
module | 4 years ago | |
sequences | 4 years ago | |
.gitignore | 4 years ago | |
README.md | 3 years ago | |
inference_our.py | 4 years ago | |
inference_real.py | 4 years ago | |
sample_msa_from_pssm.py | 4 years ago |
The paper "PSSM-Distil: Protein Secondary Structure Prediction (PSSP) on Low-QualityPSSM by Knowledge Distillation with Contrastive Learning" of AAAI21 Conference
Requirement
pip install torch
pip install glob
pip install tqdm
pip install numpy
Instructions
python inference_real.py
Aboving command will predict secondary structure for a sequence in 'sequences' folder with a pssm in 'low_pssm' folder and print the accuracy.
python inference_our.py
Aboving command will predict secondary structure of sequence in 'sequences' folder with enhanced pssm which refined by PSSM-Distil and print the accuracy.
Besides, this command will save an enhanced pssm file in 'enhanced_pssms' folder.
python sample_msa_from_pssm.py ./enhanced_pssms/4ynhA.npy
Aboving command will sample 2000 MSAs from enhanced PSSM and save in a3ms folder as '4ynhA_enhanced_pssms.a3m'.
Visualization
Please upload original low-quality .a3m file and the enhanced one in 'a3ms' folder to the website: https://weblogo.berkeley.edu/logo.cgi respectively.
Then you will see such comparison images.
BC40 dataset
https://drive.google.com/drive/folders/15vwRo_OjAkhhwfjDk6-YoKGf4JzZXIMC?usp=sharing
The dataset we released to examine the performance of PSSM-Distil
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