M
Mingyue Zheng
Researcher at Chinese Academy of Sciences
Publications - 273
Citations - 5783
Mingyue Zheng is an academic researcher from Chinese Academy of Sciences. The author has contributed to research in topics: Medicine & Biology. The author has an hindex of 34, co-authored 215 publications receiving 3867 citations. Previous affiliations of Mingyue Zheng include Ocean University of China & Southern Medical University.
Papers
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Journal ArticleDOI
Pushing the Boundaries of Molecular Representation for Drug Discovery with the Graph Attention Mechanism.
Zhaoping Xiong,Zhaoping Xiong,Dingyan Wang,Xiaohong Liu,Xiaohong Liu,Feisheng Zhong,Xiaozhe Wan,Xutong Li,Zhaojun Li,Xiaomin Luo,Kaixian Chen,Kaixian Chen,Hualiang Jiang,Hualiang Jiang,Mingyue Zheng +14 more
TL;DR: A new graph neural network architecture called Attentive FP for molecular representation that uses a graph attention mechanism to learn from relevant drug discovery datasets and achieves state-of-the-art predictive performances on a variety of datasets and that what it learns is interpretable.
Journal ArticleDOI
In silico ADME/T modelling for rational drug design
Yulan Wang,Jing Xing,Yuan Xu,Nannan Zhou,Jianlong Peng,Zhaoping Xiong,Xian Liu,Xiaomin Luo,Cheng Luo,Kaixian Chen,Mingyue Zheng,Hualiang Jiang +11 more
TL;DR: The development of in silico models for some physicochemical parameters, ADME properties and toxicity evaluation, with an emphasis on the modelling approaches thereof, their application in drug discovery, and the potential merits or deficiencies of these models are introduced.
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Preclinical characterization of anlotinib, a highly potent and selective vascular endothelial growth factor receptor-2 inhibitor.
TL;DR: Results indicate that anlotinib is a well‐tolerated, orally active VEGFR2 inhibitor that targets angiogenesis in tumor growth, and support ongoing clinical evaluation of anlot inib for a variety of malignancies.
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TransformerCPI: improving compound-protein interaction prediction by sequence-based deep learning with self-attention mechanism and label reversal experiments.
Lifan Chen,Xiaoqin Tan,Dingyan Wang,Feisheng Zhong,Xiaohong Liu,Xiaohong Liu,Tianbiao Yang,Xiaomin Luo,Kaixian Chen,Kaixian Chen,Hualiang Jiang,Hualiang Jiang,Mingyue Zheng +12 more
TL;DR: New datasets specific for CPI prediction are constructed, a novel transformer neural network named TransformerCPI is proposed, and a more rigorous label reversal experiment is introduced to test whether a model learns true interaction features.
Journal ArticleDOI
Magnetic properties of nanosized MnFe2O4 particles
TL;DR: In this article, a nano-nodes of MnFe2O4 particles were prepared by chemical ultrasonic emulsion method and as-prepared sample was found to be in amorphous state and showed spin-glass behavior at low temperature.