DeepSub

Introduction

DeepSub is a tool designed to predict the number of subunits in a protein sequence for homo-oligomers.

Installation

$ 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

Notebooks

1. 01_GetData.ipynb

   • Obtaining and processing data sets .

2. 02_SeqIdentity.ipynb

   • Sequence Identity Comparison Result.

3. 03_DeepSub.ipynb

   • DeepSub model and cross-validation results.

4. 04_Queen.ipynb

   • Queen model for model comparison.

5. 05_OpenSet.ipynb

   • OpenSet Dataset Evaluation.

Scripts

• featurizer.py

  • Sequence features are extracted before model training.

• trainer.py

  • Single training function.

Notice

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.

How to cite:

Rui Deng, Ke Wu, Jiawei Lin, Dehang Wang, Yuanyuan Huang, Yang Li, Zhenkun Shi, Zihan Zhang, Zhiwen Wang, Zhitao Mao, XiaopingLiao and Hongwu Ma, DeepSub: Utilizing Deep Learning for Predicting the Number of Subunits in Homo-Oligomeric Protein Complexes,International Journal of Molecular Sciences, 2024; https://doi.org/10.3390/ijms25094803