Skip to content

Neurotoxic peptide estimation via a convolutional neural network model

Notifications You must be signed in to change notification settings

bzlee-bio/NT_estimation

Repository files navigation

Prediction of spider novel neurotoxic peptides & peptide data augmentation

There are two tools that are proposed in the research.

  1. Prediction of spider neurotoxic peptide from amino acid sequences only.
  2. Data augmentation tool for peptide data



Prediction tools for neurotoxic peptide

Dependencies

To install python dependencies for neurotoxic peptides, run: pip install -r requirements_neurotox_pred.txt

Input file

Input file type is fasta format in which amino acids are represented using single-letter codes.

Detailed information of fasta links: https://en.wikipedia.org/wiki/FASTA_format

Output file

Output file only contains peptide list which are predicted as neurotoxin.

Running prediction of spider novel neurotoxic peptides

python ntest.py --fasta <input_fasta_file.fasta> --output <output_file_name.csv>

Data augmentation for proteins

Dependencies

To install python dependencies, run: pip install -r requirements.txt
Also, NCBI BLAST should be installed.

After install NCBI blast, BLAST bin path in aug_config.ini file should be modified.



Installation of NCBI BLAST

Ubuntu / Debian

Run $ sudo apt-get install ncbi-blast

CenotOS

  1. Download latest BLAST version (Link)
  2. Decompress $ tar -zxvf ncbi-blast-version_info-linux.tar.gz

Input file

Input file type is fasta format in which amino acids are represented using single-letter codes.

Detailed information of fasta links: https://en.wikipedia.org/wiki/FASTA_format

Output file

Output file contains information about probabilities of four respective ion-channel modulability.

Probability with >=0.5 predicts as modulator peptides for respective ion channels.

Running a data augmentation tool

python peptide_augmentation.py --fasta <input_fasta_file.fasta> --cpu <max_cpu_usage> --eval <E-value cutoff>

Citation

Lee, Byungjo, Min K. Shin, In-Wook Hwang, Junghyun Jung, Yu J. Shim, Go W. Kim, Seung T. Kim, Wonhee Jang, and Jung-Suk Sung. 2021. "A Deep Learning Approach with Data Augmentation to Predict Novel Spider Neurotoxic Peptides" International Journal of Molecular Sciences 22, no. 22: 12291. https://doi.org/10.3390/ijms222212291

About

Neurotoxic peptide estimation via a convolutional neural network model

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published

Languages