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个人简介
My research interest combines computational and experimental approaches for pathogen and cancer research. On the computational side, my group is both developing and applying the latest deep learning technologies to analyze a wide range of biological and biochemical data, including (i) developing Artificial Intelligence (AI)-powered smart microscopic imaging to accelerate disease diagnostic and drug discovery. (ii) enabling deep learning techniques to be applied to omics data, (e.g. modeling of proteins, DNAs, miRNAs, LncRNAs, and mRNAs and their interactions, structures and/or dynamics in molecular, cellular and tissue level), for the discovery of novel diagnostic biomarkers and therapeutic targets. (iii) the use of deep learning in cheminformatics and chemical biology in guiding drug discovery to target those therapeutic targets and fight against disease. On the experimental side, my group combines imaging, high-throughput sequencing, mass spectrometry, and chemical biology to mechanistically understand diseases at the molecular level by addressing the fundamental question of how those molecules shape the disease systematically.
研究兴趣
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TRENDS IN GENETICSno. 1 (2024): 94-107
TRAC-TRENDS IN ANALYTICAL CHEMISTRY (2024): 117540
PROCEEDINGS OF THE 17TH ACM INTERNATIONAL CONFERENCE ON WEB SEARCH AND DATA MINING, WSDM 2024 (2024): 28-37
Dandan Zhu,Mo-Fan Huang,An Xu, Xueqin Gao, Yu-Wen Huang, Trinh T T Phan,Linchao Lu,Ting-Yen Chi,Yulin Dai,Lon Kai Pang,Julian A Gingold, Jian Tu,
The Journal of biological chemistryno. 8 (2024): 107494-107494
ACM TRANSACTIONS ON KNOWLEDGE DISCOVERY FROM DATAno. 1 (2024): 1-21
Trends in Parasitologyno. 7 (2024): 633-646
Yang Zhang, Yongen Li
Journal of medicinal chemistryno. 24 (2023): 16568-16578
Yao Wang,Yang Zhang,Peng-Chao Li, Jiajie Guo,Fan Huo,Jintao Yang,Ru Jia, Juan Wang,Qiju Huang,Dan Theodorescu,Hanyang Yu,Chao Yan
crossref(2023)
PROCEEDINGS OF THE 17TH ACM CONFERENCE ON RECOMMENDER SYSTEMS, RECSYS 2023 (2023): 1007-1014
PROCEEDINGS OF THE 17TH ACM CONFERENCE ON RECOMMENDER SYSTEMS, RECSYS 2023 (2023): 993-999
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