Title: Deep learning enables accurate prediction of interplay between lncRNA and disaeas

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1.data

The experimental data are downloaded from LncRNADiseas2.0 database

2.Implementation

NNLDA is implemented in Python 3.5 and use Tensorflow 1.12.0. Package numpy and pandas are also required.

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This section introduces how to run NNLDA to make prediction

Train model(model will save in ./model)

  python train_model.py

make prediciton

  python make_prediction.py

Then you need to enter the name of the disease which you need to predict. A scoring file will be generater when the prediciton is completed