CGABepi: A deep learning framework for linear B cell epitope prediction using physicochemical property encoding

Introduction

CGABepi is a deep learning framework for linear B cell epitope prediction.

Prerequisites:

All environmental information can be found in "environment.yaml".

data preparation: You can customize your file source and output location to your needs in the '# configue' block at the end of the file 'codes/indep_test.py'.

Also, you can select suitable model for your prediction through modifying the 'model_save_dir_name'. You can choose 4 models, and the names of the models are in the 'models' folder.

For a more detailed description of the model, please refer to the paper: CGABepi: A deep learning framework for linear B cell epitope prediction using physicochemical property encoding