Jun Qin

16.5k total citations · 1 hit paper
233 papers, 13.2k citations indexed

About

Jun Qin is a scholar working on Molecular Biology, Cell Biology and Immunology and Allergy. According to data from OpenAlex, Jun Qin has authored 233 papers receiving a total of 13.2k indexed citations (citations by other indexed papers that have themselves been cited), including 121 papers in Molecular Biology, 64 papers in Cell Biology and 63 papers in Immunology and Allergy. Recurrent topics in Jun Qin's work include Cell Adhesion Molecules Research (63 papers), Cellular Mechanics and Interactions (27 papers) and Protein Structure and Dynamics (14 papers). Jun Qin is often cited by papers focused on Cell Adhesion Molecules Research (63 papers), Cellular Mechanics and Interactions (27 papers) and Protein Structure and Dynamics (14 papers). Jun Qin collaborates with scholars based in United States, China and France. Jun Qin's co-authors include Edward F. Plow, Chuanyue Wu, Brian T. Chait, Angela M. Gronenborn, Olga Vinogradova, G. Marius Clore, Xiaolong Zhang, Yan-Qing Ma, Vasily Ogryzko and Koichi Fukuda and has published in prestigious journals such as Nature, Cell and Proceedings of the National Academy of Sciences.

In The Last Decade

Jun Qin

220 papers receiving 13.0k citations

Hit Papers

Involvement of the TIP60 Histone Acetylase Complex in DNA... 2000 2026 2008 2017 2000 250 500 750

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Jun Qin United States 62 8.4k 3.3k 2.9k 1.6k 1.1k 233 13.2k
Yasuhiro Yamada Japan 63 9.8k 1.2× 3.3k 1.0× 2.3k 0.8× 1.1k 0.7× 262 0.2× 482 16.7k
Lan Bo Chen United States 58 7.7k 0.9× 1.3k 0.4× 2.1k 0.7× 1.4k 0.9× 263 0.2× 128 12.7k
Michael J.O. Wakelam United Kingdom 64 10.5k 1.3× 487 0.1× 2.5k 0.9× 1.6k 1.0× 1.4k 1.3× 241 15.0k
Roger J. Daly Australia 59 10.5k 1.3× 1.1k 0.3× 2.2k 0.7× 1.4k 0.9× 272 0.3× 173 14.0k
Patrick J. Casey United States 74 14.8k 1.8× 761 0.2× 3.5k 1.2× 1.1k 0.7× 318 0.3× 247 19.3k
Mark A. Lemmon United States 78 18.3k 2.2× 1.2k 0.4× 7.1k 2.4× 2.1k 1.3× 423 0.4× 159 25.5k
Matthias P. Wymann Switzerland 58 9.0k 1.1× 960 0.3× 1.7k 0.6× 3.9k 2.4× 146 0.1× 138 14.6k
Karl R. Clauser United States 49 7.2k 0.9× 507 0.2× 1.5k 0.5× 1.5k 0.9× 3.0k 2.8× 84 11.6k
Walter Kölch Ireland 81 18.9k 2.3× 623 0.2× 3.7k 1.3× 2.0k 1.3× 980 0.9× 298 25.5k
Giulio Superti‐Furga Austria 77 13.5k 1.6× 528 0.2× 2.1k 0.7× 4.1k 2.6× 981 0.9× 247 21.7k

Countries citing papers authored by Jun Qin

Since Specialization
Citations

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

Fields of papers citing papers by Jun Qin

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jun Qin

This figure shows the co-authorship network connecting the top 25 collaborators of Jun Qin. A scholar is included among the top collaborators of Jun Qin 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 Jun Qin. Jun Qin 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.
Pluskota, Elżbieta, Dorota Szpak, Yunmei Wang, et al.. (2025). Kindlin-3 phosphorylation is crucial for thrombosis and hemostasis in vivo. Research and Practice in Thrombosis and Haemostasis. 9(3). 102863–102863.
2.
Chen, Liwei, et al.. (2025). The Bidirectional Relationship Between Subjective Well-Being and Depression: A Cross-Sectional and Cross-Lagged Network Analysis. Psychology Research and Behavior Management. Volume 18. 719–731. 1 indexed citations
3.
Chen, Ming, et al.. (2024). The “toxic window” of amoxicillin exposure during pregnancy on long bone development in fetal mice. Life Sciences. 350. 122759–122759. 2 indexed citations
4.
Liu, Fei, et al.. (2023). Influence of intermetallics and element concentrations on the performance of the heat treated HVDC AlSiMgMnCu alloys at nano-scale. Materials & Design. 229. 111902–111902. 7 indexed citations
5.
Li, Gao, et al.. (2023). Stepwise correction of ECMWF ensemble forecasts of severe rainfall in China based on segmented hierarchical clustering. Frontiers in Earth Science. 10. 1 indexed citations
6.
Szpak, Dorota, Katarzyna Białkowska, Kamila Bledzka, et al.. (2023). Kindlin-3 deficiency leads to impaired erythropoiesis and erythrocyte cytoskeleton. Blood Advances. 7(9). 1739–1753. 5 indexed citations
7.
Shangguan, Yangfan, Xufeng Li, Jun Qin, et al.. (2022). Positive programming of the GC-IGF1 axis mediates adult osteoporosis susceptibility in male offspring rats induced by prenatal dexamethasone exposure. Biochemical Pharmacology. 206. 115264–115264. 9 indexed citations
9.
Bertolini, Irene, Jagadish C. Ghosh, Andrew V. Kossenkov, et al.. (2020). Small Extracellular Vesicle Regulation of Mitochondrial Dynamics Reprograms a Hypoxic Tumor Microenvironment. Developmental Cell. 55(2). 163–177.e6. 34 indexed citations
10.
Bromberger, Thomas, Liang Zhu, Sarah Klapproth, Jun Qin, & Markus Moser. (2019). Rap1 and membrane lipids cooperatively recruit talin to trigger integrin activation. Journal of Cell Science. 132(21). 34 indexed citations
11.
Bromberger, Thomas, Sarah Klapproth, Ina Rohwedder, et al.. (2018). Direct Rap1/Talin1 interaction regulates platelet and neutrophil integrin activity in mice. Blood. 132(26). 2754–2762. 53 indexed citations
12.
Chen, Xing, Gang Cai, Caini Liu, et al.. (2018). IL-17R–EGFR axis links wound healing to tumorigenesis in Lrig1+ stem cells. The Journal of Experimental Medicine. 216(1). 195–214. 88 indexed citations
13.
Chen, Biao, et al.. (2013). Association between severity of knee osteoarthritis and serum and synovial fluid interleukin 17 concentrations. Journal of International Medical Research. 42(1). 138–144. 69 indexed citations
14.
Das, Mitali, Sujay Subbayya Ithychanda, Jun Qin, & Edward F. Plow. (2013). Mechanisms of talin-dependent integrin signaling and crosstalk. Biochimica et Biophysica Acta (BBA) - Biomembranes. 1838(2). 579–588. 97 indexed citations
15.
Qin, Jun & Thomas Fahringer. (2012). Scientific Workflows: Programming, Optimization, and Synthesis with ASKALON and AWDL. DIAL (Catholic University of Leuven). 13 indexed citations
16.
Yang, Jun, Yan-Qing Ma, Richard C. Page, et al.. (2009). Structure of an integrin αIIbβ3 transmembrane-cytoplasmic heterocomplex provides insight into integrin activation. Proceedings of the National Academy of Sciences. 106(42). 17729–17734. 125 indexed citations
17.
Qin, Jun, et al.. (2009). Fallen temperature effects at green patches of urban residential areas and analysis of its influence factors.. Zhiwu ziyuan yu huanjing. 18(3). 50–55. 3 indexed citations
18.
Csanády, László, Donna Seto‐Young, Kim W. Chan, et al.. (2005). Preferential Phosphorylation of R-domain Serine 768 Dampens Activation of CFTR Channels by PKA. The Journal of General Physiology. 125(2). 171–186. 59 indexed citations
19.
Qin, Jun. (2004). Study and Implementation of Message Communication Based on MSMQ. Computer and Modernization.
20.
Travaglini‐Allocatelli, Carlo, Francesca Cutruzzolà, Andrea Brancaccio, et al.. (1993). Structural and functional characterization of sperm whale myoglobin mutants: Role of arginine (E10) in ligand stabilization. Biochemistry. 32(23). 6041–6049. 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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