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MAHyNet: Parallel Hybrid Network for RNA-Protein Binding Sites Prediction Based on Multi-Head Attention and Expectation pooling

Introduction


In this work, a new parallel network that integrates the multi-head attention mechanism and the expectation pooling is proposed, named MAHyNet. The left-branch network of this model mixes convolutional neural network and gated recurrent neural network, and its right-branch network is a two-layer convolutional neural network, which can extract the features of one-hot and RNA base physicochemical properties, respectively.


Requirements


  • Keras = 2.1.6
  • tensorflow-gpu =1.8.0
  • h5py
  • pool
  • tqdm
  • sklearn

Non-10-fold cross-validation


python generate_hdf5.py
python generate_hdf5_ph.py
python train_data.py 0 0 53 
python save_result.py

10-fold cross-validation


python generate_hdf5_10.py 
python generate_hdf5_10ph.py
python train_ten_data.py 0 0 53  
python see_10_fold.py  

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