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PhosPPI: a Sequence-based Machine Learning Method for Predicting the Effects of Phosphorylation on Protein-Protein Interactions

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PhosPPI

A web service (PhosPPI) for Sequence-based Machine Learning Method for Predicting the Effects of Phosphorylation on Protein-Protein Interactions created by Xiaokun Hong, Jiyang Lv

Citation

Hong X, Lv J, Li Z, Xiong Y, Zhang J*, Chen HF*. Sequence-based machine learning method for predicting the effects of phosphorylation on protein-protein interactions. Int J Biol Macromol. 2023 Jul 15;243:125233. doi: 10.1016/j.ijbiomac.2023.125233. Epub 2023 Jun 6. PMID: 37290543.

Contact

<1>[email protected] <2>[email protected]

Set up environment

  1. Our Conda environment was created based on NetSurfP-3.0's Conda environment (Nucleic Acids Res,2022). *https://services.healthtech.dtu.dk/service.php?NetSurfP-3.0
  • conda env create --file environment.yml
  • conda activate nsp3
  • python setup.py install
  • pip3 install -r requirements.txt

*In addition, Web service and Machine Learning Python packages are required to install according to the following instructions:

  1. Install Web Service Python packages
  • pip install
    • Flask=1.1.2
    • Flask-WTF=1.1.1
    • WTForms=3.0.1
    • Flask-Bootstrap=3.3.7.1
    • Jinja2=2.11.3
    • pandas=1.2.3
    • gunicorn=19.9.0
  1. Other packages no need to install (latest version up to 2022-02-16; best to install them as network connection from China may fail)
  1. To perform PSI-BLAST to obtain PSSM features, ncbi-blast-2.9.0+-x64-linux are also needed to install. *https://ftp.ncbi.nlm.nih.gov/blast/executables/blast+/2.9.0/

  2. Install Machine Learning Python packages

  • pip install sklearn=0.0
  • pip install lightgbm=3.3.3

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PhosPPI: a Sequence-based Machine Learning Method for Predicting the Effects of Phosphorylation on Protein-Protein Interactions

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