Y
Yadi Zhou
Researcher at Cleveland Clinic Lerner Research Institute
Publications - 68
Citations - 5045
Yadi Zhou is an academic researcher from Cleveland Clinic Lerner Research Institute. The author has contributed to research in topics: Medicine & Biology. The author has an hindex of 18, co-authored 46 publications receiving 3082 citations. Previous affiliations of Yadi Zhou include Ohio University & East China University of Science and Technology.
Papers
More filters
Journal ArticleDOI
admetSAR: a comprehensive source and free tool for assessment of chemical ADMET properties.
TL;DR: An ADMET structure-activity relationship database that collects, curates, and manages available ADMET-associated properties data from the published literature, and provides a user-friendly interface to query a specific chemical profile, using either CAS registry number, common name, or structure similarity.
Journal ArticleDOI
Network-based drug repurposing for novel coronavirus 2019-nCoV/SARS-CoV-2
Yadi Zhou,Yuan Hou,Jiayu Shen,Yin Huang,William R. Martin,Feixiong Cheng,Feixiong Cheng,Feixiong Cheng +7 more
TL;DR: This study presents an integrative, antiviral drug repurposing methodology implementing a systems pharmacology-based network medicine platform, quantifying the interplay between the HCoV–host interactome and drug targets in the human protein–protein interaction network.
Journal ArticleDOI
Artificial intelligence in COVID-19 drug repurposing.
TL;DR: This Review provides a strong rationale for using AI-based assistive tools for drug repurposing medications for human disease, including during the COVID-19 pandemic.
Journal ArticleDOI
deepDR: a network-based deep learning approach to in silico drug repositioning.
Xiangxiang Zeng,Siyi Zhu,Xiangrong Liu,Yadi Zhou,Ruth Nussinov,Feixiong Cheng,Feixiong Cheng,Feixiong Cheng +7 more
TL;DR: A network-based deep-learning approach for in silico drug repurposing by integrating 10 networks, termed deepDR, which learns high-level features of drugs from the heterogeneous networks by a multimodal deep autoencoder and infer candidates for approved drugs for which they were not originally approved.
Journal ArticleDOI
Target identification among known drugs by deep learning from heterogeneous networks.
Xiangxiang Zeng,Siyi Zhu,Weiqiang Lu,Zehui Liu,Jin Huang,Yadi Zhou,Jiansong Fang,Yin Huang,Yin Huang,Huimin Guo,Lang Li,Bruce D. Trapp,Ruth Nussinov,Ruth Nussinov,Charis Eng,Joseph Loscalzo,Feixiong Cheng,Feixiong Cheng,Feixiong Cheng +18 more
TL;DR: DeepDTnet offers a powerful network-based deep learning methodology for target identification to accelerate drug repurposing and minimize the translational gap in drug development.