DeepSub is a tool designed to predict the number of subunits in a protein sequence for homo-oligomers.
$ git clone https://github.com/tibbdc/DeepSub.git
$ cd DeepSub
$ conda create -n deepsub python=3.9
$ conda activate deepsub
$ pip install -r requirements.txt
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01_GetData.ipynb
- Obtaining and processing data sets .
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02_SeqIdentity.ipynb
- Sequence Identity Comparison Result.
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03_DeepSub.ipynb
- DeepSub model and cross-validation results.
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04_Queen.ipynb
- Queen model for model comparison.
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05_OpenSet.ipynb
- OpenSet Dataset Evaluation.
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featurizer.py
- Sequence features are extracted before model training.
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trainer.py
- Single training function.
We have successfully trained the model, which is now stored at DeepSub/model/deepsub.h5. You can simply execute the test.ipynb notebook to start making predictions. Should you wish to retrain the model with your custom dataset, please refer to the instructions in the "Usage" section and adjust accordingly.