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    Drug Side-Effect Prediction Using Heterogeneous Features and Bipartite Local Models

    Yi Zheng1,2, Wentao Zhao2,*, Chengcheng Sun2, Qian Li1

    CMC-Computers, Materials & Continua, Vol.60, No.2, pp. 481-496, 2019, DOI:10.32604/cmc.2019.05536

    Abstract Drug side-effects impose massive costs on society, leading to almost one-third drug failure in the drug discovery process. Therefore, early identification of potential side-effects becomes vital to avoid risks and reduce costs. Existing computational methods employ few drug features and predict drug side-effects from either drug side or side-effect side separately. In this work, we explore to predict drug side-effects by combining heterogeneous drug features and employing the bipartite local models (BLMs) which fuse predictions from both the drug side and side-effect side. Specifically, we integrate drug chemical structures, drug interacted proteins and drug associated genes into a unified framework… More >

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