DMFLDA is a deep learning framework for predicting lncRNA–disease associations.
tensorflow==1.3.0
numpy==1.11.2
scikit-learn==0.18
scipy==0.18.1
In this GitHub project, we give a demo to show how DMFLDA works. In data_processing folder, we give three datasets we used in our study.
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interMatrix.mat is the raw lncRNA-disease interaction matrix with matlab format. Its shape is 577 lncRNAs x 272 diseases.
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matrix.npy is the lncRNA-disease interaction matrix with numpy format.
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data.pkl is used to store the sampled positive and negative samples.
You can use these python files which provided by us in data_processing folder to obtain them.
In our demo, we provide a leave-one-out cross validation to evaluate our model. You can use cross_validation.py to see experimental results and predict lncRNA related diseases. If you want to tune some hyper-parameters, you can change some values of hyper-parameters in hyperparams.py.
The other details can see the paper and the codes.
This project is licensed under the MIT License - see the LICENSE.txt file for details