Biosynthetic Gene Cluster finder with Graph Neural Network
Project description
# BGCfinder : Biosynthetic Gene Cluster detection with Graph Neural Network
BGCfinder detects biosynthetic gene clusters in bacterial genomes using deep learning. BGCfinder takes a fasta file containing bacterial protein coding sequences and embed each protein sequence into a graph. Graph Neural Network takes the graphs to detect biosynthetic gene cluster.
Author : Jihun Jeung, jihun@gm.gist.ac.kr, jeung4705@gmail.com, https://github.com/jihunni/BGCfinder
To construct the conda environment, `bash $ conda create --name BGCfinder --clone base $ conda init bash $ conda activate BGCfinder $ conda install pytorch cudatoolkit=11.3 -c pytorch $ conda install pyg -c pyg $ pip install `
To run BGCfinder with a fasta file containing amino acid sequence with CPU, `bash python BGCfinder/main.py data/test_run.fasta -o test_run.tsv -l test_run.log -d False `
To run BGCfinder with a fasta file containing amino acid sequence with GPU, `bash python BGCfinder/main.py data/test_run.fasta -o test_run.tsv -l test_run.log -d True `
The development environment of BGCfinder : ` 'torch==1.10.0', 'torch-geometric==2.0.2', 'torch-scatter==2.0.9', 'torch-sparse==0.6.12' `
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