This repository provides the scripts used to produce the data used in the paper Computational design of peptide therapeutics: how useful are sequence-based protein-protein interaction predictors? by Charih et al.
The experiments were all performed in a Linux environment, with no expectation that this could be reproduced on Windows.
- Francois Charih francois@charih.ca
- Kyle K. Biggar kyle_biggar@carleton.ca
- James R. Green jrgreen@sce.carleton.ca
The data preparation and analysis is written in Julia, so you will need Julia 1.6 installed on your machine to run this. In addition to Julia, the following libraries are required:
- FASTX
- CSV
- ArgParse
- DataFrames
- Plots
To run this code, you will need to have the following softare installed on your path.
The predictors used are available in their respective repositories.
- D-SCRIPT and its pre-trained weights
- PIPR
- SPRINT
To produce the data in the data folder, one can run the script prepare_datasets.sh.
The predictors can then be trained according to the instructions on the produced training data and then used to predict the interactions between the therapeutic peptides and the human proteome.
The code used to analyze the results is available in notebooks/Plotting.ipynb.
Copyright (c) 2021 Carleton University Biomedical Informatics Collaboratory
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