Herb Target Prediction Based on Representation Learning of Symptom related Heterogeneous Network.
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ABSTRACT:
SUBMITTER: Wang N
PROVIDER: S-EPMC6396098 | biostudies-literature | 2019
REPOSITORIES: biostudies-literature
Publications
Herb Target Prediction Based on Representation Learning of Symptom related Heterogeneous Network.
Wang Ning N Li Peng P Hu Xiaochen X Yang Kuo K Peng Yonghong Y Zhu Qiang Q Zhang Runshun R Gao Zhuye Z Xu Hao H Liu Baoyan B Chen Jianxin J Zhou Xuezhong X
Computational and structural biotechnology journal 20190208
Traditional Chinese Medicine (TCM) has received increasing attention as a complementary approach or alternative to modern medicine. However, experimental methods for identifying novel targets of TCM herbs heavily relied on the current available herb-compound-target relationships. In this work, we present an Herb-Target Interaction Network (HTINet) approach, a novel network integration pipeline for herb-target prediction mainly relying on the symptom related associations. HTINet focuses on captur ...[more]
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