Shaoyu Wang

4.5k total citations
113 papers, 3.2k citations indexed

About

Shaoyu Wang is a scholar working on Molecular Biology, Radiology, Nuclear Medicine and Imaging and Pediatrics, Perinatology and Child Health. According to data from OpenAlex, Shaoyu Wang has authored 113 papers receiving a total of 3.2k indexed citations (citations by other indexed papers that have themselves been cited), including 29 papers in Molecular Biology, 15 papers in Radiology, Nuclear Medicine and Imaging and 14 papers in Pediatrics, Perinatology and Child Health. Recurrent topics in Shaoyu Wang's work include Probability and Risk Models (11 papers), Insurance, Mortality, Demography, Risk Management (11 papers) and Insurance and Financial Risk Management (10 papers). Shaoyu Wang is often cited by papers focused on Probability and Risk Models (11 papers), Insurance, Mortality, Demography, Risk Management (11 papers) and Insurance and Financial Risk Management (10 papers). Shaoyu Wang collaborates with scholars based in China, Australia and United States. Shaoyu Wang's co-authors include Joshua Sumankuuro, Judith Crockett, Zhengguang Wang, Jingjie Liang, Jan Dhaene, Feng‐Sheng Wang, Janice R. Aldrich‐Wright, Vincent J. Higgins, Harry H. Panjer and Yushan Chen and has published in prestigious journals such as SHILAP Revista de lepidopterología, PLoS ONE and Advanced Functional Materials.

In The Last Decade

Shaoyu Wang

107 papers receiving 3.0k citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Shaoyu Wang China 30 824 618 589 496 477 113 3.2k
Charles Brown United States 47 151 0.2× 1.8k 3.0× 1.2k 2.0× 95 0.2× 249 0.5× 122 8.1k
Thomas J. George United States 40 348 0.4× 1.1k 1.7× 848 1.4× 1.8k 3.7× 29 0.1× 415 7.4k
William W. Davis United States 40 147 0.2× 766 1.2× 358 0.6× 200 0.4× 41 0.1× 110 6.2k
Yoram Weiss Israel 43 203 0.2× 2.5k 4.0× 578 1.0× 216 0.4× 1.2k 2.6× 151 8.3k
Yuyu Chen China 27 82 0.1× 845 1.4× 436 0.7× 59 0.1× 165 0.3× 76 4.0k
Chia‐Lin Chang Taiwan 33 163 0.2× 1.8k 3.0× 281 0.5× 731 1.5× 59 0.1× 235 4.3k
Alistair S. Hall United Kingdom 46 55 0.1× 1.3k 2.1× 925 1.6× 325 0.7× 27 0.1× 184 8.8k
John Morgan United States 38 493 0.6× 631 1.0× 666 1.1× 222 0.4× 42 0.1× 142 4.8k
Joon‐Young Park United States 34 127 0.2× 2.2k 3.6× 766 1.3× 1.1k 2.2× 21 0.0× 130 4.9k

Countries citing papers authored by Shaoyu Wang

Since Specialization
Citations

This map shows the geographic impact of Shaoyu Wang's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Shaoyu Wang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Shaoyu Wang more than expected).

Fields of papers citing papers by Shaoyu Wang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Shaoyu Wang. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Shaoyu Wang. The network helps show where Shaoyu Wang may publish in the future.

Co-authorship network of co-authors of Shaoyu Wang

This figure shows the co-authorship network connecting the top 25 collaborators of Shaoyu Wang. A scholar is included among the top collaborators of Shaoyu Wang based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Shaoyu Wang. Shaoyu Wang is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
2.
Xu, Jiaojiao, Xin Wen, Shaoyu Wang, et al.. (2025). Identification of key species and molecular mechanisms driving conjugative transfer of antibiotic resistance genes in swine manure-derived bacterial communities. Journal of Hazardous Materials. 497. 139638–139638.
3.
Cui, Long, Zhaoqi Wang, Keke Zhao, et al.. (2024). Multiple diffusion models for predicting pathologic response of esophageal squamous cell carcinoma to neoadjuvant chemotherapy. Abdominal Radiology. 49(12). 4216–4226.
4.
Wang, Shaoyu, et al.. (2023). Predictive Taxonomy Analytics (LASSO): Predicting Outcome Types of Cyber Breach. DR-NTU (Nanyang Technological University). 9(1).
5.
Qu, Jinrong, Yu‐Dong Zhang, Shuang Lü, et al.. (2022). Quantitative RECIST derived from multiparametric MRI in evaluating response of esophageal squamous cell carcinoma to neoadjuvant therapy. European Radiology. 32(10). 7295–7306. 11 indexed citations
6.
Lian, Wei‐Shiung, Re‐Wen Wu, Jih‐Yang Ko, et al.. (2022). Histone H3K27 demethylase UTX compromises articular chondrocyte anabolism and aggravates osteoarthritic degeneration. Cell Death and Disease. 13(6). 538–538. 14 indexed citations
7.
Wang, Peng, Jinlong He, Xueying Ma, et al.. (2022). Applying MAP-MRI to Identify the WHO Grade and Main Genetic Features of Adult-type Diffuse Gliomas: A Comparison of Three Diffusion-weighted MRI Models. Academic Radiology. 30(7). 1238–1246. 12 indexed citations
8.
Zhang, Huiting, Xu Yan, Shaoyu Wang, et al.. (2021). Whole-Tumor Histogram Analysis of Multiple Diffusion Metrics for Glioma Genotyping. Radiology. 302(3). 652–661. 52 indexed citations
9.
Li, Xue‐Ming, Yang Liu, Yi Wang, et al.. (2021). DCE-MRI of esophageal carcinoma using star-VIBE compared with conventional 3D-VIBE. Scientific Reports. 11(1). 24091–24091. 4 indexed citations
10.
Khan, Ajab, Panpan Sun, Yaogui Sun, et al.. (2021). Curcumol inhibits encephalomyocarditis virus by promoting IFN-β secretion. BMC Veterinary Research. 17(1). 318–318. 14 indexed citations
11.
Tan, Qiang, Shuang Shi, Jingjie Liang, et al.. (2020). Endometrial cell-derived small extracellular vesicle miR-100-5p promotes functions of trophoblast during embryo implantation. Molecular Therapy — Nucleic Acids. 23. 217–231. 40 indexed citations
12.
Ma, Keran, Xiaonan Zhang, Huiting Zhang, et al.. (2020). Mean apparent propagator-MRI: A new diffusion model which improves temporal lobe epilepsy lateralization. European Journal of Radiology. 126. 108914–108914. 24 indexed citations
13.
Cheng, Jia, et al.. (2020). Chlorogenic acid rescues zearalenone induced injury to mouse ovarian granulosa cells. Ecotoxicology and Environmental Safety. 194. 110401–110401. 36 indexed citations
14.
Lian, Wei‐Shiung, Jih‐Yang Ko, Yushan Chen, et al.. (2019). MicroRNA-29a represses osteoclast formation and protects against osteoporosis by regulating PCAF-mediated RANKL and CXCL12. Cell Death and Disease. 10(10). 705–705. 55 indexed citations
15.
Dong, Xin, Shaoyu Wang, Lian Xu, Juan Lin, & Xinqi Xu. (2019). Inhibitory mechanism of Penicillin V on mushroom tyrosinase. Molecular Biology Reports. 47(2). 967–975. 8 indexed citations
16.
17.
Sumankuuro, Joshua, Judith Crockett, & Shaoyu Wang. (2018). Perceived barriers to maternal and newborn health services delivery: a qualitative study of health workers and community members in low and middle-income settings. BMJ Open. 8(11). e021223–e021223. 70 indexed citations
18.
Sumankuuro, Joshua, Judith Crockett, & Shaoyu Wang. (2016). Antenatal care on the Agenda of the Post-Millennium Development Goals in northern Ghana. Charles Sturt University Research Output (CRO). 18(2). 341–352. 5 indexed citations
19.
Lin, Chun‐Liang, Yung‐Chien Hsu, Pei‐Hsien Lee, et al.. (2014). Cannabinoid receptor 1 disturbance of PPARγ2 augments hyperglycemia induction of mesangial inflammation and fibrosis in renal glomeruli. Journal of Molecular Medicine. 92(7). 779–792. 36 indexed citations
20.
Zhang, Lang, Yumin Li, Yuhong Jing, et al.. (2013). Protective effects of carbenoxolone are associated with attenuation of oxidative stress in ischemic brain injury. Neuroscience Bulletin. 29(3). 311–320. 25 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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