Zobrazeno 1 - 10
of 57
pro vyhledávání: '"Tingyang Xu"'
Autor:
Lei Huang, Tingyang Xu, Yang Yu, Peilin Zhao, Xingjian Chen, Jing Han, Zhi Xie, Hailong Li, Wenge Zhong, Ka-Chun Wong, Hengtong Zhang
Publikováno v:
Nature Communications, Vol 15, Iss 1, Pp 1-16 (2024)
Abstract Structure-based generative chemistry is essential in computer-aided drug discovery by exploring a vast chemical space to design ligands with high binding affinity for targets. However, traditional in silico methods are limited by computation
Externí odkaz:
https://doaj.org/article/d069f7e7892d451bafdf42d21076f3b3
Autor:
Xiaochu Tong, Dingyan Wang, Xiaoyu Ding, Xiaoqin Tan, Qun Ren, Geng Chen, Yu Rong, Tingyang Xu, Junzhou Huang, Hualiang Jiang, Mingyue Zheng, Xutong Li
Publikováno v:
Journal of Cheminformatics, Vol 14, Iss 1, Pp 1-15 (2022)
Abstract Blood–brain barrier is a pivotal factor to be considered in the process of central nervous system (CNS) drug development, and it is of great significance to rapidly explore the blood–brain barrier permeability (BBBp) of compounds in sili
Externí odkaz:
https://doaj.org/article/9a7ddcb8597d432f8d6f9b87974e8c61
Publikováno v:
Computational and Structural Biotechnology Journal, Vol 20, Iss , Pp 2839-2847 (2022)
Repositioning or repurposing drugs account for a substantial part of entering approval pipeline drugs, which indicates that drug repositioning has huge market potential and value. Computational technologies such as machine learning methods have accel
Externí odkaz:
https://doaj.org/article/a0ff253cb2fc4394aaef611c067ae487
Autor:
Yang Yu, Tingyang Xu, Jiawen Li, Yaping Qiu, Yu Rong, Zhen Gong, Xuemin Cheng, Liming Dong, Wei Liu, Jin Li, Dengfeng Dou, Junzhou Huang
Publikováno v:
ACS Omega, Vol 6, Iss 35, Pp 22945-22954 (2021)
Externí odkaz:
https://doaj.org/article/106912b400cd4818b51eb35927b32c61
Autor:
Qifeng Bai, Jian Ma, Shuo Liu, Tingyang Xu, Antonio Jesús Banegas-Luna, Horacio Pérez-Sánchez, Yanan Tian, Junzhou Huang, Huanxiang Liu, Xiaojun Yao
Publikováno v:
Computational and Structural Biotechnology Journal, Vol 19, Iss , Pp 3573-3579 (2021)
Artificial intelligence can train the related known drug data into deep learning models for drug design, while classical algorithms can design drugs through established and predefined procedures. Both deep learning and classical algorithms have their
Externí odkaz:
https://doaj.org/article/82a60e26d61540a59e317a7abf1148ed
Autor:
Yang Yu, Junhong Huang, Hu He, Jing Han, Geyan Ye, Tingyang Xu, Xianqiang Sun, Xiumei Chen, Xiaoming Ren, Chunlai Li, Huijuan Li, Wei Huang, Yangyang Liu, Xinjuan Wang, Yongzhi Gao, Nianhe Cheng, Na Guo, Xibo Chen, Jianxia Feng, Yuxia Hua, Chong Liu, Guoyun Zhu, Zhi Xie, Lili Yao, Wenge Zhong, Xinde Chen, Wei Liu, Hailong Li
Publikováno v:
ACS Medicinal Chemistry Letters. 14:297-304
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::c73db8910c8f2071e78fb665160a3975
https://doi.org/10.1021/acsmedchemlett.2c00515
https://doi.org/10.1021/acsmedchemlett.2c00515
Publikováno v:
IEEE Transactions on Information Forensics and Security. 18:2104-2118
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::70fd29b84ab1942e6555c4ee3c87f697
https://doi.org/10.1109/tifs.2023.3254449
https://doi.org/10.1109/tifs.2023.3254449
Autor:
KO-SHIN CHEN1, TINGYANG XU2, GUANNAN LIANG1, QIANQIAN TONG1, MINGHU SONG3, JINBO BI1 jinbo.bi@uconn.com
Publikováno v:
Journal of Data Science. Apr2022, Vol. 20 Issue 2, p228-252. 25p.
Publikováno v:
Proceedings of the ACM Web Conference 2023.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::a508f3d48fa355105c8204845794839d
https://doi.org/10.1145/3543507.3583211
https://doi.org/10.1145/3543507.3583211
Autor:
Hehuan Ma, Yatao Bian, Yu Rong, Wenbing Huang, Tingyang Xu, Weiyang Xie, Geyan Ye, Junzhou Huang
Publikováno v:
Bioinformatics. 38:2003-2009
Motivation The crux of molecular property prediction is to generate meaningful representations of the molecules. One promising route is to exploit the molecular graph structure through graph neural networks (GNNs). Both atoms and bonds significantly
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::248bec37f7bd463e7386937c1e8c4691
https://doi.org/10.1093/bioinformatics/btac039
https://doi.org/10.1093/bioinformatics/btac039