Dao-Yan Pan

753 total citations · 1 hit paper
8 papers, 502 citations indexed

About

Dao-Yan Pan is a scholar working on Endocrinology, Diabetes and Metabolism, Molecular Biology and Rehabilitation. According to data from OpenAlex, Dao-Yan Pan has authored 8 papers receiving a total of 502 indexed citations (citations by other indexed papers that have themselves been cited), including 4 papers in Endocrinology, Diabetes and Metabolism, 2 papers in Molecular Biology and 2 papers in Rehabilitation. Recurrent topics in Dao-Yan Pan's work include Diabetic Foot Ulcer Assessment and Management (2 papers), Wound Healing and Treatments (2 papers) and Liver Disease and Transplantation (1 paper). Dao-Yan Pan is often cited by papers focused on Diabetic Foot Ulcer Assessment and Management (2 papers), Wound Healing and Treatments (2 papers) and Liver Disease and Transplantation (1 paper). Dao-Yan Pan collaborates with scholars based in China, Australia and Macao. Dao-Yan Pan's co-authors include Jie Shen, Jiayi Yang, Zhiyi Chen, Huai Li, Siyu Wang, Cory J. Xian, Quan Zhou, Jie Shen, Qing Chen and Gustavo Duque and has published in prestigious journals such as The Journal of Clinical Endocrinology & Metabolism, International Journal of Nanomedicine and Calcified Tissue International.

In The Last Decade

Dao-Yan Pan

8 papers receiving 498 citations

Hit Papers

<p>Umbilical Cord-Derived Mesenchymal Stem Cell-Der... 2020 2026 2022 2024 2020 100 200 300

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Dao-Yan Pan China 4 278 226 157 148 65 8 502
Jianlong Su China 10 238 0.9× 259 1.1× 75 0.5× 127 0.9× 53 0.8× 13 521
Julin Xie China 15 369 1.3× 200 0.9× 123 0.8× 118 0.8× 46 0.7× 17 658
Longqing Wang China 6 167 0.6× 319 1.4× 119 0.8× 64 0.4× 48 0.7× 11 540
Kyoung-Mi Lee South Korea 11 222 0.8× 172 0.8× 91 0.6× 199 1.3× 53 0.8× 13 648
Alireza Hassanshahi Iran 7 211 0.8× 126 0.6× 108 0.7× 88 0.6× 46 0.7× 8 441
Zhenxing Si China 6 247 0.9× 82 0.4× 235 1.5× 132 0.9× 67 1.0× 7 473
Dahai Hu China 10 174 0.6× 215 1.0× 63 0.4× 102 0.7× 35 0.5× 21 463
Luosha Gu China 5 164 0.6× 198 0.9× 77 0.5× 67 0.5× 25 0.4× 12 385
Khadijeh Falahzadeh Iran 10 136 0.5× 174 0.8× 112 0.7× 69 0.5× 23 0.4× 15 422
Xiao-jie Tan China 2 160 0.6× 191 0.8× 74 0.5× 64 0.4× 25 0.4× 4 328

Countries citing papers authored by Dao-Yan Pan

Since Specialization
Citations

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

Fields of papers citing papers by Dao-Yan Pan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Dao-Yan Pan. 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 Dao-Yan Pan. The network helps show where Dao-Yan Pan may publish in the future.

Co-authorship network of co-authors of Dao-Yan Pan

This figure shows the co-authorship network connecting the top 25 collaborators of Dao-Yan Pan. A scholar is included among the top collaborators of Dao-Yan Pan 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 Dao-Yan Pan. Dao-Yan Pan is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

8 of 8 papers shown
1.
Chen, Xingying, Dongmei Wang, Zhi Chen, et al.. (2025). Inflammatory and metabolic markers mediate the association of hepatic steatosis and fibrosis with 10-year ASCVD risk. Annals of Medicine. 57(1). 2486594–2486594. 1 indexed citations
2.
Chen, Zhi, D. Song, Dao-Yan Pan, et al.. (2023). A Randomized Clinical Trial of Intravenous Methylprednisolone With 2 Protocols in Patients With Graves Orbitopathy. The Journal of Clinical Endocrinology & Metabolism. 109(1). 36–45. 1 indexed citations
3.
Xu, Lin, Xiang‐He Meng, Xiao Wang, et al.. (2022). Identification of PDXDC1 as a novel pleiotropic susceptibility locus shared between lumbar spine bone mineral density and birth weight. Journal of Molecular Medicine. 100(5). 723–734. 1 indexed citations
4.
Zeng, Canjun, Qing Chen, Haifeng Huang, et al.. (2020). HNGF6A Inhibits Oxidative Stress-Induced MC3T3-E1 Cell Apoptosis and Osteoblast Phenotype Inhibition by Targeting Circ_0001843/miR-214 Pathway. Calcified Tissue International. 106(5). 518–532. 22 indexed citations
5.
Yang, Jiayi, Zhiyi Chen, Dao-Yan Pan, Huai Li, & Jie Shen. (2020). <p>Umbilical Cord-Derived Mesenchymal Stem Cell-Derived Exosomes Combined Pluronic F127 Hydrogel Promote Chronic Diabetic Wound Healing and Complete Skin Regeneration</p>. International Journal of Nanomedicine. Volume 15. 5911–5926. 374 indexed citations breakdown →
6.
Wang, Xiao, et al.. (2020). Conditional knockout of pyruvate dehydrogenase in mouse pancreatic β‑cells causes morphological and functional changes. Molecular Medicine Reports. 21(4). 1717–1726. 4 indexed citations
7.
Wang, Siyu, et al.. (2017). Adipose-derived stem cells seeded in Pluronic F-127 hydrogel promotes diabetic wound healing. Journal of Surgical Research. 217. 63–74. 96 indexed citations
8.
Fan, Lijun, Wei Jiang, Heng Wan, et al.. (2016). [Prevalence of chronic kidney disease and its risk factors in subjects with different glucose metabolism status].. PubMed. 36(5). 697–700. 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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