Ying Dong

4.6k total citations · 1 hit paper
121 papers, 3.1k citations indexed

About

Ying Dong is a scholar working on Molecular Biology, Surgery and Cardiology and Cardiovascular Medicine. According to data from OpenAlex, Ying Dong has authored 121 papers receiving a total of 3.1k indexed citations (citations by other indexed papers that have themselves been cited), including 40 papers in Molecular Biology, 23 papers in Surgery and 23 papers in Cardiology and Cardiovascular Medicine. Recurrent topics in Ying Dong's work include Gut microbiota and health (14 papers), Immune Cell Function and Interaction (9 papers) and Diet and metabolism studies (7 papers). Ying Dong is often cited by papers focused on Gut microbiota and health (14 papers), Immune Cell Function and Interaction (9 papers) and Diet and metabolism studies (7 papers). Ying Dong collaborates with scholars based in China, United States and Singapore. Ying Dong's co-authors include Zengwu Wang, Zuo Chen, Congyi Zheng, Linfeng Zhang, Lan Shao, Guang Hao, Manlu Zhu, Runlin Gao, Jiali Wang and Ye Tian and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Circulation and Journal of Clinical Investigation.

In The Last Decade

Ying Dong

113 papers receiving 3.1k citations

Hit Papers

Status of Hypertension in China 2018 2026 2020 2023 2018 250 500 750 1000

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Ying Dong China 27 860 775 421 389 362 121 3.1k
Seong Kwon South Korea 32 592 0.7× 774 1.0× 312 0.7× 485 1.2× 140 0.4× 243 3.4k
Andrzej Tykarski Poland 26 628 0.7× 447 0.6× 315 0.7× 415 1.1× 419 1.2× 247 2.6k
Xiang Xie China 25 1.1k 1.2× 831 1.1× 587 1.4× 590 1.5× 154 0.4× 186 4.6k
Dingli Xu China 34 1.5k 1.7× 1.3k 1.7× 393 0.9× 332 0.9× 241 0.7× 161 3.9k
Naga Venkata K. Pothineni United States 21 1.2k 1.4× 827 1.1× 474 1.1× 653 1.7× 185 0.5× 133 3.7k
Chih‐Wei Yang Taiwan 27 555 0.6× 909 1.2× 641 1.5× 747 1.9× 289 0.8× 81 5.3k
Beata Franczyk Poland 29 516 0.6× 813 1.0× 434 1.0× 451 1.2× 175 0.5× 130 3.0k
Sorin Ursoniu Romania 29 380 0.4× 625 0.8× 417 1.0× 841 2.2× 214 0.6× 123 3.2k
Toshiki Moriyama Japan 43 948 1.1× 1.3k 1.7× 652 1.5× 738 1.9× 416 1.1× 220 5.5k
Qian Deng China 22 430 0.5× 814 1.1× 800 1.9× 365 0.9× 354 1.0× 95 3.0k

Countries citing papers authored by Ying Dong

Since Specialization
Citations

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

Fields of papers citing papers by Ying Dong

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Ying Dong

This figure shows the co-authorship network connecting the top 25 collaborators of Ying Dong. A scholar is included among the top collaborators of Ying Dong 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 Ying Dong. Ying Dong 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.
Zhao, Jianyu, Zewen Sun, Zesheng An, et al.. (2025). MicroRNA ‐mediated Ets1 repression in retinal endothelial cells: A novel anti‐angiogenic mechanism in nonproliferative diabetic retinopathy. Diabetes Obesity and Metabolism. 27(4). 1888–1901. 2 indexed citations
2.
Dong, Ying, Xiang Li, Sixiang Wen, et al.. (2025). Healthcare function differences between Ziqin & Kujin (Scutellaria baicalensis): Role of component proportions. Applied Food Research. 5(2). 101290–101290.
3.
Wang, Pan, Yang Shen, Jie Jiao, et al.. (2025). CKD patients comorbid with hypertension are associated with imbalanced gut microbiome. iScience. 28(2). 111766–111766. 3 indexed citations
4.
Li, Jing, et al.. (2024). Alteration of the intestinal microbiota and serum metabolites in a mouse model of Pon1 gene ablation. The FASEB Journal. 38(7). e23611–e23611. 1 indexed citations
6.
Feng, Peng, Piergiorgio Cao, Sili Ren, et al.. (2024). The mechanical and hydrochemical properties of cemented calcareous soil under long-term soaking. Scientific Reports. 14(1). 24532–24532. 3 indexed citations
7.
Lu, Xiaobing, Jiang Yue, Qianjing Liu, et al.. (2023). Thigh muscle fat fraction is independently associated with impaired glucose metabolism in individuals with obesity. Endocrine Connections. 12(11). 5 indexed citations
8.
Shen, Yang, Ying Dong, Jie Jiao, et al.. (2023). BBIBP-CorV Vaccination against the SARS-CoV-2 Virus Affects the Gut Microbiome. Vaccines. 11(5). 942–942. 6 indexed citations
9.
Wang, Pan, et al.. (2023). Untargeted metabolomics unravel serum metabolic alterations in smokers with hypertension. Frontiers in Physiology. 14. 1127294–1127294. 5 indexed citations
10.
Dong, Ying, et al.. (2022). Potential of gut microbiota for lipopolysaccharide biosynthesis in European women with type 2 diabetes based on metagenome. Frontiers in Cell and Developmental Biology. 10. 1027413–1027413. 6 indexed citations
11.
Song, Juanjuan, Mei Yang, Ying Liu, et al.. (2021). Elabela prevents angiotensin II-induced apoptosis and inflammation in rat aortic adventitial fibroblasts via the activation of FGF21–ACE2 signaling. Journal of Molecular Histology. 52(5). 905–918. 17 indexed citations
12.
Liu, Yijun, et al.. (2021). Identification of New Genes and Loci Associated With Bone Mineral Density Based on Mendelian Randomization. Frontiers in Genetics. 12. 728563–728563. 4 indexed citations
13.
Wang, Zengwu, Xin Wang, Guang Hao, et al.. (2018). A national study of the prevalence and risk factors associated with peripheral arterial disease from China: The China Hypertension Survey, 2012–2015. International Journal of Cardiology. 275. 165–170. 32 indexed citations
14.
Zhao, Yanhong, et al.. (2017). Time-series analysis in imatinib-resistant chronic myeloid leukemia K562-cells under different drug treatments. Journal of Huazhong University of Science and Technology [Medical Sciences]. 37(4). 621–627. 4 indexed citations
15.
Dong, Ying, et al.. (2017). MiR-186 Inhibited Migration of NSCLC via Targeting cdc42 and Effecting EMT Process. Molecules and Cells. 40(3). 195–201. 29 indexed citations
16.
Dai, Jiaqi, Hongxia Wang, Ying Dong, Yinxin Zhang, & Jian Wang. (2013). Bile Acids Affect the Growth of Human Cholangiocarcinoma via NF-kB Pathway. Cancer Investigation. 31(2). 111–120. 37 indexed citations
17.
Dong, Ying, et al.. (2012). Study on the current situation of medical waste management. World Automation Congress. 1–3. 1 indexed citations
18.
Li, Xinxing, Ying Dong, Wei Wang, et al.. (2012). Emodin As an Effective Agent in Targeting Cancer Stem-Like Side Population Cells of Gallbladder Carcinoma. Stem Cells and Development. 22(4). 554–566. 62 indexed citations
19.
Dai, Jiaqi, Hongxia Wang, Yihui Shi, et al.. (2011). Impact of bile acids on the growth of human cholangiocarcinoma via FXR. Journal of Hematology & Oncology. 4(1). 41–41. 67 indexed citations
20.
Emmanouilidis, Nikos, Zhong Guo, Ying Dong, et al.. (2006). Immunosuppressive and Trafficking Properties of Donor Splenic and Bone Marrow Dendritic Cells. Transplantation. 81(3). 455–462. 15 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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