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Xiangtai Kong

Showing results (1-10 of 12) with videos related to

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Trends in Endocrinology and Metabolism: TEM|March 9, 2026
Targeting mitochondrial metabolism with combined metabolic activatorsHong Yang, Xiangtai Kong, Xinmeng Liao, et al.
Briefings in Bioinformatics|February 23, 2024
TG468: a text graph convolutional network for predicting clinical response to immune checkpoint inhibitor therapyKun Wang, Jiangshan Shi, Xiaochu Tong, et al.
Briefings in Bioinformatics|November 26, 2024
miCGR: interpretable deep neural network for predicting both site-level and gene-level functional targets of microRNAXiaolong Wu, Lehan Zhang, Xiaochu Tong, et al.
Iscience|February 9, 2026
Machine learning identifies proteomic risk factors across 23 diseasesLingqi Meng, Mengzhen Li, Xiangtai Kong, et al.
Nature Communications|June 25, 2024
Deep representation learning of chemical-induced transcriptional profile for phenotype-based drug discoveryXiaochu Tong, Ning Qu, Xiangtai Kong, et al.
Computational and Structural Biotechnology Journal|July 23, 2025
Anticancer effects and mechanisms of <i>Pulsatilla chinensis</i>, <i>Bupleurum chinense</i> and <i>Polyporus umbellatus</i> on human lung carcinoma and hepatoma cellsMengzhen Li, Woonghee Kim, Han Jin, et al.
Nature Computational Science|January 4, 2024
Computing the relative binding affinity of ligands based on a pairwise binding comparison networkJie Yu, Zhaojun Li, Geng Chen, et al.
Briefings in Bioinformatics|December 19, 2023
KinomeMETA: meta-learning enhanced kinome-wide polypharmacology profilingQun Ren, Ning Qu, Jingjing Sun, et al.
Proceedings of the National Academy of Sciences of the United States of America|December 24, 2025
Flexible protein-ligand docking with diffusion-based side-chain packingRunze Zhang, Xinyu Jiang, Duanhua Cao, et al.
Journal of Medicinal Chemistry|February 21, 2023
Structural Optimization of Fibroblast Growth Factor Receptor Inhibitors for Treating Solid TumorsChunpu Li, Yang Dai, Xiangtai Kong, et al.
Pageof 2

Showing results (1-10 of 12) with videos related to

Sort By:
Pageof 2
Trends in Endocrinology and Metabolism: TEM|March 9, 2026
Targeting mitochondrial metabolism with combined metabolic activatorsHong Yang, Xiangtai Kong, Xinmeng Liao, et al.
Briefings in Bioinformatics|February 23, 2024
TG468: a text graph convolutional network for predicting clinical response to immune checkpoint inhibitor therapyKun Wang, Jiangshan Shi, Xiaochu Tong, et al.
Briefings in Bioinformatics|November 26, 2024
miCGR: interpretable deep neural network for predicting both site-level and gene-level functional targets of microRNAXiaolong Wu, Lehan Zhang, Xiaochu Tong, et al.
Iscience|February 9, 2026
Machine learning identifies proteomic risk factors across 23 diseasesLingqi Meng, Mengzhen Li, Xiangtai Kong, et al.
Nature Communications|June 25, 2024
Deep representation learning of chemical-induced transcriptional profile for phenotype-based drug discoveryXiaochu Tong, Ning Qu, Xiangtai Kong, et al.
Computational and Structural Biotechnology Journal|July 23, 2025
Anticancer effects and mechanisms of <i>Pulsatilla chinensis</i>, <i>Bupleurum chinense</i> and <i>Polyporus umbellatus</i> on human lung carcinoma and hepatoma cellsMengzhen Li, Woonghee Kim, Han Jin, et al.
Nature Computational Science|January 4, 2024
Computing the relative binding affinity of ligands based on a pairwise binding comparison networkJie Yu, Zhaojun Li, Geng Chen, et al.
Briefings in Bioinformatics|December 19, 2023
KinomeMETA: meta-learning enhanced kinome-wide polypharmacology profilingQun Ren, Ning Qu, Jingjing Sun, et al.
Proceedings of the National Academy of Sciences of the United States of America|December 24, 2025
Flexible protein-ligand docking with diffusion-based side-chain packingRunze Zhang, Xinyu Jiang, Duanhua Cao, et al.
Journal of Medicinal Chemistry|February 21, 2023
Structural Optimization of Fibroblast Growth Factor Receptor Inhibitors for Treating Solid TumorsChunpu Li, Yang Dai, Xiangtai Kong, et al.
Pageof 2