Yingjun Su

1.2k total citations
21 papers, 900 citations indexed

About

Yingjun Su is a scholar working on Oncology, Immunology and Dermatology. According to data from OpenAlex, Yingjun Su has authored 21 papers receiving a total of 900 indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Oncology, 7 papers in Immunology and 6 papers in Dermatology. Recurrent topics in Yingjun Su's work include Chemokine receptors and signaling (6 papers), Dermatologic Treatments and Research (5 papers) and Mesenchymal stem cell research (4 papers). Yingjun Su is often cited by papers focused on Chemokine receptors and signaling (6 papers), Dermatologic Treatments and Research (5 papers) and Mesenchymal stem cell research (4 papers). Yingjun Su collaborates with scholars based in China, United States and Australia. Yingjun Su's co-authors include Ann Richmond, Sandeep K. Raghuwanshi, Ricardo M. Richardson, Yingchun Yu, Vandana Singh, Tammy Sobolik, Sam Wells, Gregory D. Ayers, Mieke Gouwy and Jo Van Damme and has published in prestigious journals such as The Journal of Immunology, Cancer Research and Molecular Biology of the Cell.

In The Last Decade

Yingjun Su

20 papers receiving 884 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Yingjun Su China 10 382 341 252 109 75 21 900
Atsuhiko Kato Japan 19 228 0.6× 347 1.0× 234 0.9× 122 1.1× 65 0.9× 71 1.0k
Elizabeth K. Duperret United States 18 435 1.1× 474 1.4× 476 1.9× 143 1.3× 129 1.7× 25 1.1k
Nina Linde Germany 10 452 1.2× 346 1.0× 379 1.5× 160 1.5× 75 1.0× 17 884
Anke S. Lonsdorf Germany 16 450 1.2× 602 1.8× 652 2.6× 81 0.7× 158 2.1× 45 1.5k
Giusy Gentilcore Italy 15 526 1.4× 484 1.4× 478 1.9× 151 1.4× 57 0.8× 31 1.2k
Gerrit Erdmann Germany 14 259 0.7× 808 2.4× 136 0.5× 323 3.0× 101 1.3× 25 1.1k
Andrew Sprague United States 13 209 0.5× 421 1.2× 745 3.0× 141 1.3× 81 1.1× 17 1.4k
Anastasia Chillà Italy 23 265 0.7× 667 2.0× 234 0.9× 336 3.1× 92 1.2× 45 1.1k
Ann Richmond United States 17 682 1.8× 704 2.1× 594 2.4× 260 2.4× 160 2.1× 37 1.5k
Azadeh Arabzadeh Canada 11 357 0.9× 538 1.6× 259 1.0× 131 1.2× 41 0.5× 20 1.0k

Countries citing papers authored by Yingjun Su

Since Specialization
Citations

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

Fields of papers citing papers by Yingjun Su

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Yingjun Su

This figure shows the co-authorship network connecting the top 25 collaborators of Yingjun Su. A scholar is included among the top collaborators of Yingjun Su 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 Yingjun Su. Yingjun Su 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.
Su, Yingjun, et al.. (2022). LARP6 Regulates Keloid Fibroblast Proliferation, Invasion, and Ability to Synthesize Collagen. Journal of Investigative Dermatology. 142(9). 2395–2405.e7. 9 indexed citations
2.
3.
Chen, Lin, Xi Zhang, Zhou Yu, et al.. (2020). Inhibition of Notch Intracellular Domain Suppresses Cell Activation and Fibrotic Factors Production in Hypertrophic Scar Fibroblasts Versus Normal Skin Fibroblasts. Annals of Plastic Surgery. 86(4). 400–405. 2 indexed citations
4.
Chen, Lin, Jianzhang Wang, Shengxu Li, et al.. (2018). The clinical dynamic changes of macrophage phenotype and function in different stages of human wound healing and hypertrophic scar formation. International Wound Journal. 16(2). 360–369. 55 indexed citations
5.
Feng, Hao, Lihong Qiu, Teng Zhang, et al.. (2017). Heat-Shock Protein 70 Overexpression in Adipose-Derived Stem Cells Enhances Fat Graft Survival. Annals of Plastic Surgery. 78(4). 460–466. 4 indexed citations
6.
7.
Sobolik, Tammy, Yingjun Su, Sam Wells, et al.. (2014). CXCR4 drives the metastatic phenotype in breast cancer through induction of CXCR2 and activation of MEK and PI3K pathways. Molecular Biology of the Cell. 25(5). 566–582. 74 indexed citations
8.
Chen, Jianwu, et al.. (2014). An Alternative Model of Vascularized Bone Marrow Transplant. Annals of Plastic Surgery. 73(6). 710–715. 1 indexed citations
9.
Zhao, Jianhui, Chenggang Yi, Yan Han, et al.. (2014). Autologous Fat Graft and Bone Marrow–Derived Mesenchymal Stem Cells Assisted Fat Graft for Treatment of Parry-Romberg Syndrome. Annals of Plastic Surgery. 73(Supplement 1). S99–S103. 29 indexed citations
10.
Hao, Xiaoyan, Teng Zhang, Yang Yang, et al.. (2013). Morphological Features of Cell Death and Tissue Remolding of Fat Grafts. Annals of Plastic Surgery. 74(6). 722–727. 9 indexed citations
11.
Sobolik, Tammy, Yingjun Su, Sam Wells, & Ann Richmond. (2013). Abstract A53: CXCR4 drives the metastatic phenotype in breast cancer through induction of CXCR2, transactivation of HER2/EGFR, and activation of MEK and PI3K pathways. Cancer Research. 73(3_Supplement). A53–A53. 1 indexed citations
12.
Shi, Jihong, Dahai Hu, Zhanfeng Zhang, et al.. (2012). Reduced expression of microtubule-associated protein 1 light chain 3 in hypertrophic scars. Archives of Dermatological Research. 304(3). 209–215. 31 indexed citations
13.
Liu, Yan, Oriana E. Hawkins, Yingjun Su, et al.. (2012). Targeting aurora kinases limits tumour growth through DNA damage‐mediated senescence and blockade of NF‐κB impairs this drug‐induced senescence. EMBO Molecular Medicine. 5(1). 149–166. 78 indexed citations
14.
Raghuwanshi, Sandeep K., et al.. (2012). The Chemokine Receptors CXCR1 and CXCR2 Couple to Distinct G Protein-Coupled Receptor Kinases To Mediate and Regulate Leukocyte Functions. The Journal of Immunology. 189(6). 2824–2832. 123 indexed citations
15.
Bai, Xiaozhi, Dahai Hu, Li Bai, et al.. (2012). [Effects of myrrh extract on proliferation and collagen mRNA expression of human fibroblasts in vitro].. PubMed. 28(2). 130–3. 3 indexed citations
16.
Thu, Yee Mon, Yingjun Su, Jinming Yang, Ryan Splittgerber, & Ann Richmond. (2011). Abstract 2889: NF-κB inducing kinase modulates melanoma tumorigenesis by regulating pro-survival factors through β-catenin. Cancer Research. 71(8_Supplement). 2889–2889. 1 indexed citations
17.
Richmond, Ann & Yingjun Su. (2008). Mouse xenograft models vs GEM models for human cancer therapeutics. Disease Models & Mechanisms. 1(2-3). 78–82. 314 indexed citations
18.
Yu, Yingchun, Yingjun Su, Susan R. Opalenik, et al.. (2008). Short tail with skin lesion phenotype occurs in transgenic mice with keratin-14 promoter-directed expression of mutant CXCR2. Journal of Leukocyte Biology. 84(2). 406–419. 1 indexed citations
19.
Schutyser, Evemie, Yingjun Su, Yingchun Yu, et al.. (2007). Hypoxia enhances CXCR4 expression in human microvascular endothelial cells and human melanoma cells.. PubMed. 18(2). 59–70. 81 indexed citations
20.
Su, Yingjun, Sandeep K. Raghuwanshi, Yingchun Yu, et al.. (2005). Altered CXCR2 Signaling in β-Arrestin-2-Deficient Mouse Models. The Journal of Immunology. 175(8). 5396–5402. 74 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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