Deep Learning Neural Network Development for the Classification of Bacteriocin Sequences Produced by Lactic Acid Bacteria

This project contains the following underlying data:

      Software-Related Files

               ·         BacLABNet_script.ipynb (Deep Learning Neural Network for classification of Bacteriocin Sequences) 

               ·         embed_proteins.py (Recurrent Neural Network to obtained the embedding vectors)

               ·         model_I22.h5 (This file contains the trained weights of the trained model)

               ·         model_I22.json (This file contains the structure of the trained model)

               ·         rnn_gru.pt (Initial weights of the Recurrent Neural Network to obtain embedding vectors)

               ·         List_kmers.csv (List of 5-mers and 7-mers obtained from dataset after it filtered sequences shorter than 50 aa and                           longer than 2000 aa)

      Files Used for Training, Testing, and Validation of the Neural Network

               ·         data_nonBacLAB.csv (25000 nonBacLAB amino acid sequences retrieved from Uniprot)

               ·         data_BacLAB.csv (24964 BacLAB amino acid sequences retrieved from Uniprot)

       Additional Files

                ·         data_BacLAB_and_nonBacLAB.csv (Combination of sequences from data_BacLAB.csv and data_nonBacLAB.csv)

                 ·         all k.mers list.xlsx (Table of all k-mers obtained for k=3,5,7,15,20)

Note: Codes are additionally available on GitHub. 

Data are available under the terms of the Creative Commons Zero "No rights reserved" data waiver (CC0 1.0 Public domain dedication)(http://creativecommons.org/publicdomain/zero/1.0/)