DRBP-EDP has been developed in both executable and web-based versions.

• The executable version of DRBP-EDP can be accessed and downloaded from Hugging Face.

• The web-based version involves the following steps to set up and run:

  1. Clone the Repository: First, clone the DRBP-EDP repository from GitHub to your local machine:

     git clone https://github.com/MuQiang-MQ/DRBP-EDP.git

  2. Install Conda (if not already installed): If you don't have Conda installed, download and install Anaconda or Miniconda.

  3. Create a Conda Environment: Create a new Conda environment for the project. You can specify the Python version you want to use (preferably Python 3.9 or higher) with the following command:

     conda create --name drbp-edp-env python=3.9

  4. Activate the Conda Environment: After creating the environment, activate it with:

     conda activate drbp-edp-env

  5. Install Dependencies: Ensure that you are in the root directory of the project (where requirements.txt is located). Use the following command to navigate to that directory:

     cd /d path/to/your/project

     Then, install all required dependencies by running:

     # Before running the next command, ensure the environment is activated
     pip install -r requirements.txt
     

  6. Download the Model Files: The web-based version of DRBP-EDP requires the model checkpoint files to function properly. Please visit the Hugging Face page for the model and download the model folder from this link.

     The model folder contains:

     • esm2_t33_650M_UR50D (the model checkpoint file)
     • best_model_stage1.pth
     • best_model_stage2.pth

     After downloading, place these files into the DRBP-EDP folder.

  7. Verify the Directory Structure: Ensure that the directory structure looks like the following:

     DRBP-EDP/
      ├── drbp_edp_web_local.py
      ├── requirements.txt
      ├── icon.ico
      ├── model/                  <-- This should contain the downloaded model files
      │   ├── esm2_t33_650M_UR50D
      │   ├── best_model_stage1.pth
      │   ├── best_model_stage2.pth
      ├── ... (other files and directories)
     

  8. Run the Web-Based Application: Now you are ready to run the web application. In the terminal, from the project directory, execute:

     streamlit run drbp_edp_web_local.py

     This will start a local server, and the terminal should show output similar to:

     You can now view your Streamlit app in your browser.
     Local URL:  http://localhost:8501
     Network URL:  http://<your-network-ip>:8501
     

  9. Access the Application: Once the Streamlit app is running, it should automatically open in your browser. If it doesn't, or if you want to manually check, simply open your browser and navigate to http://localhost:8501 to view and interact with the web application.

If you find this repository useful, please cite our paper:

@article{mu2025drbp,
  title={DRBP-EDP: classification of DNA-binding proteins and RNA-binding proteins using ESM-2 and dual-path neural network},
  author={Mu, Qiang and Yu, Guoping and Zhou, Guomin and He, Yubing and Zhang, Jianhua},
  journal={NAR Genomics and Bioinformatics},
  volume={7},
  number={2},
  pages={lqaf058},
  year={2025},
  publisher={Oxford University Press}
}