Due to the great importance of this issue in the economy, industry, and health, proposing appropriate computational methods for predicting unknown DDI with high precision is challenging. We propose a novel machine learning method for predicting unknown DDIs called "NDD", using a two-layer fully connected neural network. NDD uses various characteristics of drugs to have comprehensive information. Multiple drug similarities are calculated. NDD integrat various drug similarities with a non-linear similarity fusion method called "SNF" to achieve high-level features.

Link of paper: https://www.nature.com/articles/s41598-019-50121-3

• python version 3.5.3
• keras lib https://github.com/fchollet/keras/
• scikit-learn

Find DS1-Ds3 on NDD folder. Codes of functions of NDD are available in NDD folder.

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