Zhong Wang

648 total citations
42 papers, 459 citations indexed

About

Zhong Wang is a scholar working on Molecular Biology, Cancer Research and Complementary and alternative medicine. According to data from OpenAlex, Zhong Wang has authored 42 papers receiving a total of 459 indexed citations (citations by other indexed papers that have themselves been cited), including 37 papers in Molecular Biology, 9 papers in Cancer Research and 8 papers in Complementary and alternative medicine. Recurrent topics in Zhong Wang's work include Metabolomics and Mass Spectrometry Studies (13 papers), Bioinformatics and Genomic Networks (11 papers) and Traditional Chinese Medicine Analysis (7 papers). Zhong Wang is often cited by papers focused on Metabolomics and Mass Spectrometry Studies (13 papers), Bioinformatics and Genomic Networks (11 papers) and Traditional Chinese Medicine Analysis (7 papers). Zhong Wang collaborates with scholars based in China, United States and India. Zhong Wang's co-authors include Jun Liu, Yanan Yu, Bing Li, Yongyan Wang, Pengqian Wang, Mingxi Xu, Meng Gu, Jun Da, Ke Zhang and Yinying Chen and has published in prestigious journals such as PLoS ONE, Cancer Research and Scientific Reports.

In The Last Decade

Zhong Wang

38 papers receiving 455 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Zhong Wang China 13 294 74 66 53 47 42 459
Dingzhu Shen China 16 302 1.0× 47 0.6× 112 1.7× 29 0.5× 64 1.4× 32 722
Sanli Xing China 11 198 0.7× 40 0.5× 51 0.8× 24 0.5× 62 1.3× 17 492
Zhiyuan Zhu China 11 274 0.9× 42 0.6× 67 1.0× 21 0.4× 64 1.4× 33 524
Dan‐Dan Wen China 5 211 0.7× 46 0.6× 45 0.7× 27 0.5× 55 1.2× 8 441
Tian Xu China 13 171 0.6× 51 0.7× 23 0.3× 36 0.7× 57 1.2× 19 385
Caixia Wu China 9 175 0.6× 41 0.6× 48 0.7× 20 0.4× 74 1.6× 18 495
Junguo Ren China 11 248 0.8× 107 1.4× 88 1.3× 19 0.4× 76 1.6× 30 509
Shuai‐nan Zhang China 13 265 0.9× 116 1.6× 28 0.4× 30 0.6× 85 1.8× 37 524
Xiaoting Luo China 12 193 0.7× 37 0.5× 49 0.7× 32 0.6× 62 1.3× 26 477

Countries citing papers authored by Zhong Wang

Since Specialization
Citations

This map shows the geographic impact of Zhong 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 Zhong Wang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Zhong Wang more than expected).

Fields of papers citing papers by Zhong Wang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Zhong 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 Zhong Wang. The network helps show where Zhong Wang may publish in the future.

Co-authorship network of co-authors of Zhong Wang

This figure shows the co-authorship network connecting the top 25 collaborators of Zhong Wang. A scholar is included among the top collaborators of Zhong 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 Zhong Wang. Zhong 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.
Zhang, Fei, Ziwen Wang, & Zhong Wang. (2025). Emerging Roles of Skeletal Muscle-Derived Exosomal miRNAs in Metabolic Regulation: A Perspective. Aging and Disease.
2.
3.
Zhao, Zhonglong, et al.. (2024). Metabolomics analysis of the yolk of Zhijin white goose during the embryogenesis based on LC-MS/MS. PLoS ONE. 19(2). e0297429–e0297429. 1 indexed citations
4.
Guan, Shuang, Yanan Yu, Bing Li, et al.. (2023). Discovery of Drug-Responsive Phenomic Alteration-Related Driver Genes in the Treatment of Coronary Heart Disease. Pharmacogenomics and Personalized Medicine. Volume 16. 201–217. 2 indexed citations
5.
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Wei, Mingqing, Jing Shi, Ting Li, et al.. (2022). Plasma repressor element 1-silencing transcription factor levels are decreased in patients with Alzheimer's disease. BMC Geriatrics. 22(1). 471–471.
7.
Li, Bing, Fengbin Zhang, Jun Liu, et al.. (2022). A molecular classification of gastric cancer associated with distinct clinical outcomes and validated by an XGBoost-based prediction model. Molecular Therapy — Nucleic Acids. 31. 224–240. 23 indexed citations
8.
Wang, Pengqian, Weiwei Zhou, Jun Liu, Feng Sui, & Zhong Wang. (2021). Modulome-Fangjiome Association Study (MoFAS) reveals differential target distribution among four similar fangjis (formulas). Journal of Ethnopharmacology. 279. 113822–113822. 5 indexed citations
9.
Jiang, Qingwu, Zhi Wang, Yingying Zhang, et al.. (2021). Dose-Dependent Variation of Synchronous Metabolites and Modules in a Yin/Yang Transformation Model of Appointed Ischemia Metabolic Networks. Frontiers in Neuroscience. 15. 645185–645185. 1 indexed citations
10.
Zhang, Yingying, Haixia Li, Bing Li, et al.. (2019). Genome Analysis Reveals a Synergistic Mechanism of Ursodeoxycholic Acid and Jasminoidin in Mice Brain Repair After Ischemia/Reperfusion: Crosstalk Among Muti-Pathways. Frontiers in Pharmacology. 10. 1383–1383. 3 indexed citations
11.
Zhang, Fengbin, Wenjuan Xu, Jun Liu, et al.. (2018). Optimizing miRNA-module diagnostic biomarkers of gastric carcinoma via integrated network analysis. PLoS ONE. 13(6). e0198445–e0198445. 7 indexed citations
12.
Zhou, Xuezhong, Lei Lei, Jun Liu, et al.. (2018). A Systems Approach to Refine Disease Taxonomy by Integrating Phenotypic and Molecular Networks. EBioMedicine. 31. 79–91. 36 indexed citations
13.
Yu, Yanan, Xiaoxu Zhang, Bing Li, et al.. (2016). Entropy-based divergent and convergent modular pattern reveals additive and synergistic anticerebral ischemia mechanisms. Experimental Biology and Medicine. 241(18). 2063–2074. 10 indexed citations
14.
Yu, Yanan, Zhong Wang, & Yongyan Wang. (2016). Decoding the Polyphyletic Flexibility of Allosteric Modular Networks: Progress and Perspectives. Critical Reviews in Eukaryotic Gene Expression. 26(4). 279–301. 4 indexed citations
15.
Zhu, Yan, Zhili Guo, Liangxiao Zhang, et al.. (2015). System-wide assembly of pathways and modules hierarchically reveal metabolic mechanism of cerebral ischemia. Scientific Reports. 5(1). 17068–17068. 21 indexed citations
16.
Yu, Yanan, Jun Liu, Lei Zhang, et al.. (2015). Clinical Zheng-hou Pharmacology: the Missing Link between Pharmacogenomics and Personalized Medicine?. Current Vascular Pharmacology. 13(4). 423–432. 6 indexed citations
17.
Li, Bing, Yingying Zhang, Yanan Yu, et al.. (2015). Quantitative assessment of gene expression network module-validation methods. Scientific Reports. 5(1). 15258–15258. 16 indexed citations
18.
Chen, Yinying, Zhong Wang, & Yongyan Wang. (2014). Spatiotemporal positioning of multipotent modules in diverse biological networks. Cellular and Molecular Life Sciences. 71(14). 2605–2624. 7 indexed citations
19.
Wang, Zhong, Zhiwei Jing, Liang Zhang, et al.. (2011). Fusion of core pathways reveals a horizontal synergistic mechanism underlying combination therapy. European Journal of Pharmacology. 667(1-3). 278–286. 23 indexed citations
20.
Li, Yao, Chang‐Xing Ma, Zhong Wang, et al.. (2010). A disequilibrium model for detecting genetic mutations for cancer. Journal of Theoretical Biology. 265(3). 218–224. 3 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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