A multimodal deep learning framework for predicting drug-drug interaction events.

Journal: Bioinformatics (Oxford, England)
Published Date:

Abstract

MOTIVATION: Drug-drug interactions (DDIs) are one of the major concerns in pharmaceutical research. Many machine learning based methods have been proposed for the DDI prediction, but most of them predict whether two drugs interact or not. The studies revealed that DDIs could cause different subsequent events, and predicting DDI-associated events is more useful for investigating the mechanism hidden behind the combined drug usage or adverse reactions.

Authors

  • Yifan Deng
    College of Informatics, Huazhong Agricultural University, Wuhan 430070, China.
  • Xinran Xu
    College of Informatics, Huazhong Agricultural University, Wuhan 430070, China.
  • Yang Qiu
    Key Laboratory for Advanced Materials Processing Technology, Ministry of Education, Beijing 100084, China. qiuyangdme@hotmail.com.
  • Jingbo Xia
    Tan KahKee College, Xiamen University, Xiamen, Fujian, China.
  • Wen Zhang
    Oil Crops Research Institute, Chinese Academy of Agricultural Sciences Wuhan 430062 China peiwuli@oilcrops.cn zhangqi521x@126.com +86-27-8681-2943 +86-27-8671-1839.
  • Shichao Liu