DECban: Full-length circRNA-RBP interaction sites prediction by using Double Embedding Cross branch attention Network

This repository was created for the paper <<DECban: Full-length circRNA-RBP interaction sites prediction by using Double Embedding Cross branch attention Network>>.

Consist of four parts, metric file stores taining metrics and checkpoints, prep file stores datasets and embeddings, script file stores models and requirements.txt records necessary denpendeny packages.

To reproduce this work, please follow these steps.

1. Prepare a conda virtual environment:

conda create -n decban python=3.6.2
conda activate decban
conda install pytorch==1.2.0 torchvision==0.4.0 cudatoolkit=10.0 -c pytorch
pip install -r requirements.txt

2. Download dataset from Cloud disk (password:o6tl). Unzip this file in /DECban/prep directory.

3. Run demo:

cd script
python Train.py

Then model will start training, training metrics will be saved in directory /DECban/metric/board, model checkpoint will be saved in dicrectory /DECban/metric/checkpoint.