TBiNet: A deep neural network for predicting transcription factor binding sites using attention mechanism

TBiNet is an attention-based neural network that predicts transcription factor-DNA binding in a given DNA sequence.

Paper information: Park, S., Koh, Y., Jeon, H. et al. "Enhancing the interpretability of transcription factor binding site prediction using attention mechanism", Scientific Reports (2020).

• Overview of TBiNet

Requirements

• Python (version 3.6.6, recommend installing Anaconda3)
• Numpy (version 1.14.6)
• H5py (version 2.8.0)
• Scipy (version 1.1.0)
• Sklearn (version 0.20.1)
• Theano (version 1.0.3)
• Keras (version 2.2.4, backend:theano)

Usage

Data

The ChIP-seq data used in this work can be downloaded from http://deepsea.princeton.edu/media/code/deepsea_train_bundle.v0.9.tar.gz.

Training TBiNet

train.ipynb

Testing TBiNet

test.ipynb

Contact information

For help or issues using TBiNet, please submit a GitHub issue. Please contact Sungjoon Park ([email protected]) for communication related to TBiNet.