%0 Journal Article %1 li2021trimnet %A Li, Pengyong %A Li, Yuquan %A Hsieh, Chang-Yu %A Zhang, Shengyu %A Liu, Xianggen %A Liu, Huanxiang %A Song, Sen %A Yao, Xiaojun %D 2021 %I Oxford University Press %J Briefings in Bioinformatics %K deep discovery drug learning medicine %N 4 %P bbaa266 %T TrimNet: learning molecular representation from triplet messages for biomedicine %V 22

@article{li2021trimnet, added-at = {2022-02-15T10:50:40.000+0100}, author = {Li, Pengyong and Li, Yuquan and Hsieh, Chang-Yu and Zhang, Shengyu and Liu, Xianggen and Liu, Huanxiang and Song, Sen and Yao, Xiaojun}, biburl = {https://www.bibsonomy.org/bibtex/27f48929a2d0feb8244e35a6eb43b0018/msteininger}, interhash = {9db0ece47d2d36415d12be1ad50aabc2}, intrahash = {7f48929a2d0feb8244e35a6eb43b0018}, journal = {Briefings in Bioinformatics}, keywords = {deep discovery drug learning medicine}, number = 4, pages = {bbaa266}, publisher = {Oxford University Press}, timestamp = {2022-02-15T10:50:40.000+0100}, title = {TrimNet: learning molecular representation from triplet messages for biomedicine}, volume = 22, year = 2021 }