Yuzhou Chen
University of Texas at Dallas
19 Papers
2 Citations
Yuzhou Chen is an academic researcher from University of Texas at Dallas. The author has contributed to research in topics: Medicine & Computer science. The author has an hindex of 1, co-authored 2 publications.
Chat about Author
Papers
Integrated network pharmacology and serum metabolomics approach deciphers the anti-colon cancer mechanisms of Huangqi Guizhi Wuwu Decoction
Boyu Pan,Yafei Xia,Senbiao Fang,Jun Ai,Kunpeng Wang,Jian Zhang,Chun-Jing Du,Yuzhou Chen,Liren Liu,Shu Yan +9 more
TL;DR: An integrated approach reveals a therapeutic effect of HGWD on CC, providing a valuable insight into developing strategies to predict and interpret the mechanisms of action for Chinese herbal decoctions.
A space-time flow LISA approach for panel flow data
Ran Tao,Yuzhou Chen,Jean-Claude Thill +2 more
TL;DR: This study proposes Space-Time Flow LISA, a localized spatial statistical method to analyze spatiotemporal autocorrelation of flow data, combining space-time LISA and Spatial Flow LISA, and evaluates its efficacy using synthetic data and a U.S. interstate migration case study.
6
Improving the Generation and Selection of Virtual Populations in Quantitative Systems Pharmacology Models
Theodore R. Rieger,Richard Allen,Lukas Bystricky,Yuzhou Chen,Glen Wright Colopy,Yifan Cui,Angelica Gonzalez,Yifei Liu,R. D. White,Rebecca A. Everett,Harvey Thomas Banks,Cynthia J. Musante +11 more
TL;DR: Improvements to the efficiency of generating Virtual Populations (VPops) are evaluated, which aimed to generate these populations without sacrificing diversity of the Virtual Patients’ pathophysiologies and phenotypes.
Location Optimization of COVID-19 Vaccination Sites: Case in Hillsborough County, Florida
TL;DR: In this paper , a modified two-step maximal covering location problem (MCLP) is proposed to choose the best locations for vaccination sites to maximize the number of residents who can conveniently access the sites and mitigating inequity issues by prioritizing disadvantaged population groups who live in geographic areas identified through the CDC's Social Vulnerability Index (SVI).
A new urban change detection method based on the local G and local spatial heteroscedasticity statistics
Yuzhou Chen,Ran Tao +1 more
TL;DR: In this article , the authors proposed a new method that combines two spatial statistics, namely the local G and local spatial heteroscedasticity, to assess the types of urban changes that each spatial unit has been experiencing.
2