Prediction of Immunogenic Peptides for T-Cell Immunity as Potential Epitopes for Targeted Vaccines and Targeted Immunotherapy in Lung Cancer Based on Deep Learning Using Convolutional Neural Network (CNN) Algorithms.

Prediksi Peptida untuk Imunitas Sel-T sebagai Epitop Potensial Targeted-Vaccine dan Targeted-Immunotherapy pada Kanker Paru Berbasis Deep Learning Menggunakan Algoritma Convolutional Neural Network (CNN)

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OLIMPIADE PENELIIAN SISWA INDONESIA 2024

Original work by: I Nyoman Agung Ananda Terano & Mirrabell Frederica Hadiwijono

🚀 Quick Setup Guide

Because this repository separates code from heavy datasets and model weights, you need to follow these steps to get it running on your local machine.

1. Python Environment Requirements

• Python Version: 3.11 or 3.12 is highly recommended. (Python 3.14+ is currently too new for TensorFlow packages!)
• If you just installed Python on Windows, ensure "Add Python to PATH" was checked during installation.

2. Download Dependencies

If you are using Visual Studio Code, you can instantly install all required libraries by using the built-in task:

1. Press Ctrl+Shift+P (or Cmd+Shift+P).
2. Type Tasks: Run Task and select it.
3. Choose setup.

(Alternatively, run pip install -r requirements.txt directly in your terminal).

3. Running the Model

Once everything is placed, you can run the model directly from the command line:

Single Mode (Test a specific Peptide + HLA pair):

python main.py --mode single --epitope "ALAKAAA" --hla "HLA-A*0201"

Multiple Mode (Batch Processing):

python main.py --mode multiple --intdir "data/raw/input.csv" --outdir "data/results/"

Note on TensorFlow Warnings: If you see warnings like Value in checkpoint could not be found... (root).optimizer.iter, this is completely normal! TensorFlow is just informing you that the optimizer state wasn't restored, which is expected since we are only running inference (predictions) and not training.