Could graph neural networks learn better molecular representation for drug discovery? A comparison study of descriptor-based and graph-based models
Jiang, Dejun, Wu, Zhenxing, Hsieh, Chang-Yu, Chen, Guangyong, Liao, Ben, Wang, Zhe, Shen, Chao, Cao, Dongsheng, Wu, Jian, Hou, Tingjun
Published in Journal of cheminformatics (17.02.2021)
Published in Journal of cheminformatics (17.02.2021)
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A unified drug–target interaction prediction framework based on knowledge graph and recommendation system
Ye, Qing, Hsieh, Chang-Yu, Yang, Ziyi, Kang, Yu, Chen, Jiming, Cao, Dongsheng, He, Shibo, Hou, Tingjun
Published in Nature communications (22.11.2021)
Published in Nature communications (22.11.2021)
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TrimNet: learning molecular representation from triplet messages for biomedicine
Li, Pengyong, Li, Yuquan, Hsieh, Chang-Yu, Zhang, Shengyu, Liu, Xianggen, Liu, Huanxiang, Song, Sen, Yao, Xiaojun
Published in Briefings in bioinformatics (01.07.2021)
Published in Briefings in bioinformatics (01.07.2021)
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An equivariant generative framework for molecular graph-structure Co-design
Zhang, Zaixi, Liu, Qi, Lee, Chee-Kong, Hsieh, Chang-Yu, Chen, Enhong
Published in Chemical science (Cambridge) (09.08.2023)
Published in Chemical science (Cambridge) (09.08.2023)
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Chemistry-intuitive explanation of graph neural networks for molecular property prediction with substructure masking
Wu, Zhenxing, Wang, Jike, Du, Hongyan, Jiang, Dejun, Kang, Yu, Li, Dan, Pan, Peichen, Deng, Yafeng, Cao, Dongsheng, Hsieh, Chang-Yu, Hou, Tingjun
Published in Nature communications (04.05.2023)
Published in Nature communications (04.05.2023)
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Neural predictor based quantum architecture search
Zhang, Shi-Xin, Hsieh, Chang-Yu, Zhang, Shengyu, Yao, Hong
Published in Machine learning: science and technology (01.12.2021)
Published in Machine learning: science and technology (01.12.2021)
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Transfer learning with graph neural networks for optoelectronic properties of conjugated oligomers
Lee, Chee-Kong, Lu, Chengqiang, Yu, Yue, Sun, Qiming, Hsieh, Chang-Yu, Zhang, Shengyu, Liu, Qi, Shi, Liang
Published in The Journal of chemical physics (14.01.2021)
Published in The Journal of chemical physics (14.01.2021)
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Deep Learning for Optoelectronic Properties of Organic Semiconductors
Lu, Chengqiang, Liu, Qi, Sun, Qiming, Hsieh, Chang-Yu, Zhang, Shengyu, Shi, Liang, Lee, Chee-Kong
Published in Journal of physical chemistry. C (02.04.2020)
Published in Journal of physical chemistry. C (02.04.2020)
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Heat transfer statistics in mixed quantum-classical systems
Liu, Junjie, Hsieh, Chang-Yu, Segal, Dvira, Hanna, Gabriel
Published in The Journal of chemical physics (14.12.2018)
Published in The Journal of chemical physics (14.12.2018)
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A generalized protein-ligand scoring framework with balanced scoring, docking, ranking and screening powers
Shen, Chao, Zhang, Xujun, Hsieh, Chang-Yu, Deng, Yafeng, Wang, Dong, Xu, Lei, Wu, Jian, Li, Dan, Kang, Yu, Hou, Tingjun, Pan, Peichen
Published in Chemical science (Cambridge) (02.08.2023)
Published in Chemical science (Cambridge) (02.08.2023)
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Knowledge-based BERT: a method to extract molecular features like computational chemists
Wu, Zhenxing, Jiang, Dejun, Wang, Jike, Zhang, Xujun, Du, Hongyan, Pan, Lurong, Hsieh, Chang-Yu, Cao, Dongsheng, Hou, Tingjun
Published in Briefings in bioinformatics (13.05.2022)
Published in Briefings in bioinformatics (13.05.2022)
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Introducing block design in graph neural networks for molecular properties prediction
Li, Yuquan, Li, Pengyong, Yang, Xing, Hsieh, Chang-Yu, Zhang, Shengyu, Wang, Xiaorui, Lu, Ruiqiang, Liu, Huanxiang, Yao, Xiaojun
Published in Chemical engineering journal (Lausanne, Switzerland : 1996) (15.06.2021)
Published in Chemical engineering journal (Lausanne, Switzerland : 1996) (15.06.2021)
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