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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 model image

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 (sungjoonopark@korea.ac.kr) for communication related to TBiNet.

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