Qiang Shan

5.4k total citations · 1 hit paper
72 papers, 3.7k citations indexed

About

Qiang Shan is a scholar working on Immunology, Molecular Biology and Oncology. According to data from OpenAlex, Qiang Shan has authored 72 papers receiving a total of 3.7k indexed citations (citations by other indexed papers that have themselves been cited), including 30 papers in Immunology, 24 papers in Molecular Biology and 9 papers in Oncology. Recurrent topics in Qiang Shan's work include Immune Cell Function and Interaction (18 papers), T-cell and B-cell Immunology (16 papers) and Immunotherapy and Immune Responses (8 papers). Qiang Shan is often cited by papers focused on Immune Cell Function and Interaction (18 papers), T-cell and B-cell Immunology (16 papers) and Immunotherapy and Immune Responses (8 papers). Qiang Shan collaborates with scholars based in China, United States and Denmark. Qiang Shan's co-authors include Hai‐Hui Xue, J. Scott Hale, Gordon J. Freeman, Ronald N. Germain, Helder I. Nakaya, Masao Hashimoto, Michael Y. Gerner, Tahseen H. Nasti, Se Jin Im and Haydn Kissick and has published in prestigious journals such as Nature, Journal of Biological Chemistry and Journal of Clinical Investigation.

In The Last Decade

Qiang Shan

68 papers receiving 3.7k citations

Hit Papers

Defining CD8+ T cells that provide the proliferative burs... 2016 2026 2019 2022 2016 400 800 1.2k

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Qiang Shan China 27 2.4k 1.3k 1.1k 317 243 72 3.7k
Peter Steinberger Austria 41 2.7k 1.1× 1.7k 1.3× 1.2k 1.1× 420 1.3× 230 0.9× 154 5.1k
Thomas Hehlgans Germany 29 1.9k 0.8× 662 0.5× 1.2k 1.1× 313 1.0× 168 0.7× 71 3.4k
Wiebke Hansen Germany 37 2.1k 0.9× 604 0.5× 1.2k 1.2× 307 1.0× 202 0.8× 99 3.9k
Jianfei Yang United States 22 3.0k 1.3× 940 0.7× 1.2k 1.1× 338 1.1× 84 0.3× 39 4.7k
James E. Pease United Kingdom 44 2.8k 1.2× 1.8k 1.4× 1.2k 1.2× 423 1.3× 356 1.5× 105 4.8k
Uzi Gileadi United Kingdom 33 2.2k 0.9× 1.2k 1.0× 1.6k 1.5× 388 1.2× 424 1.7× 51 4.4k
Daniela Wesch Germany 43 3.9k 1.6× 1.7k 1.3× 622 0.6× 371 1.2× 144 0.6× 113 4.9k
Sven Burgdorf Germany 25 2.3k 1.0× 390 0.3× 1.3k 1.2× 321 1.0× 131 0.5× 42 3.6k
Stefania Gallucci United States 25 2.5k 1.1× 495 0.4× 1.2k 1.2× 344 1.1× 134 0.6× 57 4.0k
Hidehiro Yamane United States 23 4.2k 1.8× 1000 0.8× 1.3k 1.2× 550 1.7× 171 0.7× 34 5.9k

Countries citing papers authored by Qiang Shan

Since Specialization
Citations

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

Fields of papers citing papers by Qiang Shan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Qiang Shan

This figure shows the co-authorship network connecting the top 25 collaborators of Qiang Shan. A scholar is included among the top collaborators of Qiang Shan 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 Qiang Shan. Qiang Shan 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.
Gong, Yuan, Wenyan Hao, Zhenzhen Dong, et al.. (2025). BCG‐Derived Outer Membrane Vesicles Induce TLR2‐Dependent Trained Immunity to Protect Against Polymicrobial Sepsis. Advanced Science. 12(37). e04101–e04101. 2 indexed citations
2.
Tian, Rui, et al.. (2025). Mining genetic loci and candidate genes related to salt tolerance traits in soybean. Scientific Reports. 15(1). 26826–26826.
3.
Li, Yue, et al.. (2025). Metabolomic and transcriptomic analyses of drought resistance mechanisms in sorghum varieties. PeerJ. 13. e19596–e19596. 1 indexed citations
4.
Shan, Qiang, Xue Wang, Hao Yang, et al.. (2024). Bacillus cereus CwpFM induces colonic tissue damage and inflammatory responses through oxidative stress and the NLRP3/NF-κB pathway. The Science of The Total Environment. 933. 173079–173079. 11 indexed citations
5.
Tang, Meihua, Qiang Shan, Yuwen Liu, & Shengli Chen. (2023). Pt loading-dependent transport kinetics and effectiveness of Pt in proton exchange membrane fuel cells. Journal of Power Sources. 567. 232966–232966. 10 indexed citations
6.
8.
Zhu, Shaoqi, Wei Hu, Xin Zhao, et al.. (2023). CTCF mediates CD8+ effector differentiation through dynamic redistribution and genomic reorganization. The Journal of Experimental Medicine. 220(4). 12 indexed citations
9.
Wang, Xuefei, Xue Wang, Jialu Zhang, et al.. (2023). Prediction and Verification of Curcumin as a Potential Drug for Inhibition of PDCoV Replication in LLC-PK1 Cells. International Journal of Molecular Sciences. 24(6). 5870–5870. 6 indexed citations
10.
Wang, Xue, Shuxian Li, Ning Liu, et al.. (2022). A Novel β-Hairpin Peptide Z-d14CFR Enhances Multidrug-Resistant Bacterial Clearance in a Murine Model of Mastitis. International Journal of Molecular Sciences. 23(9). 4617–4617. 13 indexed citations
11.
Jensen, Isaac J., Xiang Li, Patrick W. McGonagill, et al.. (2021). Sepsis leads to lasting changes in phenotype and function of memory CD8 T cells. eLife. 10. 26 indexed citations
12.
13.
Urban, Stina L., Isaac J. Jensen, Qiang Shan, et al.. (2020). Peripherally induced brain tissue–resident memory CD8+ T cells mediate protection against CNS infection. Nature Immunology. 21(8). 938–949. 79 indexed citations
14.
Shan, Qiang, et al.. (2019). Physiological Functions of Heat Shock Proteins. Current Protein and Peptide Science. 21(8). 751–760. 103 indexed citations
15.
Jensen, Isaac J., Christina S. Winborn, Peng Shao, et al.. (2018). Polymicrobial sepsis influences NK-cell-mediated immunity by diminishing NK-cell-intrinsic receptor-mediated effector responses to viral ligands or infections. PLoS Pathogens. 14(10). e1007405–e1007405. 48 indexed citations
16.
Danahy, Derek B., Scott M. Anthony, Isaac J. Jensen, et al.. (2017). Polymicrobial sepsis impairs bystander recruitment of effector cells to infected skin despite optimal sensing and alarming function of skin resident memory CD8 T cells. PLoS Pathogens. 13(9). e1006569–e1006569. 46 indexed citations
17.
Pan, Qingfei, Xiaomin Lou, Ju Zhang, et al.. (2017). Genomic variants in mouse model induced by azoxymethane and dextran sodium sulfate improperly mimic human colorectal cancer. Scientific Reports. 7(1). 25–25. 43 indexed citations
18.
Shan, Qiang, Rie Maurer, Robert A. Mitchell, et al.. (2014). Cystic Fibrosis Sputum DNA Has NETosis Characteristics and Neutrophil Extracellular Trap Release Is Regulated by Macrophage Migration-Inhibitory Factor. Journal of Innate Immunity. 6(6). 765–779. 170 indexed citations
19.
Zhu, Xu, Ju Zhang, Huiying Sun, et al.. (2014). Ubiquitination of Inositol-requiring Enzyme 1 (IRE1) by the E3 Ligase CHIP Mediates the IRE1/TRAF2/JNK Pathway. Journal of Biological Chemistry. 289(44). 30567–30577. 63 indexed citations
20.
Qin, Fanzhi & Qiang Shan. (2006). Adsorption of Cu2+ on Montmorillonite as Affected by 2,4-Dichlorophenoxyacetic Acid (2,4-D). Bulletin of Environmental Contamination and Toxicology. 76(1). 179–186. 2 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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