poncey / PreAntiCoV

Identifying anti-coronavirus peptides by incorporating different negative datasets and imbalanced learning strategies

PreAntiCOV

Glimpse

An implementation for prediction and analysis of Anti-CoV functional peptide.

How to Use

• analysis.ipynb: contains basic feature description of AAC, PHYCs, as well as classification between Anti-CoV and the other from three different sets
• classify.py: Make classification for different functional peptides set.
• ArgsClassify.py: Parameters of how to perform classification.

Requirements

We have already integrate the environment in env.yml. execute conda create -f env.yml to install packages required in a new created AMPrediction conda env.

Enter the enviornment with conda activate AMPrediction.

Steps for constructing classifiers

1. To extract features for given .fasta files, execute python feature_extract.py.
2. To establish predictors, execute classify.py. You can adjust any parameters at ArgsClassify.py.