Qixing Chen

2.0k total citations · 1 hit paper
53 papers, 1.5k citations indexed

About

Qixing Chen is a scholar working on Immunology, Molecular Biology and Epidemiology. According to data from OpenAlex, Qixing Chen has authored 53 papers receiving a total of 1.5k indexed citations (citations by other indexed papers that have themselves been cited), including 24 papers in Immunology, 16 papers in Molecular Biology and 15 papers in Epidemiology. Recurrent topics in Qixing Chen's work include Inflammation biomarkers and pathways (12 papers), Immune Response and Inflammation (12 papers) and Sepsis Diagnosis and Treatment (12 papers). Qixing Chen is often cited by papers focused on Inflammation biomarkers and pathways (12 papers), Immune Response and Inflammation (12 papers) and Sepsis Diagnosis and Treatment (12 papers). Qixing Chen collaborates with scholars based in China, United States and Germany. Qixing Chen's co-authors include Xiangming Fang, Baoli Cheng, Qiang Shu, Yue Jin, Andreas Hoeft, Frank Stüber, Shuijing Wu, Guohao Xie, Jinchao Hou and Kai Zhang and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Journal of Clinical Investigation and ACS Nano.

In The Last Decade

Qixing Chen

50 papers receiving 1.5k citations

Hit Papers

TREM2hi resident macrophages protect the septic heart by ... 2023 2026 2024 2025 2023 25 50 75 100

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Qixing Chen China 24 524 503 337 267 201 53 1.5k
Ellinor Kenne Sweden 20 811 1.5× 467 0.9× 242 0.7× 109 0.4× 132 0.7× 33 2.0k
Fabiano Pinheiro da Silva Brazil 19 396 0.8× 330 0.7× 239 0.7× 213 0.8× 100 0.5× 54 1.1k
Satoshi Ono Japan 23 684 1.3× 305 0.6× 415 1.2× 80 0.3× 200 1.0× 42 1.4k
Xueyin Shi China 20 511 1.0× 701 1.4× 179 0.5× 68 0.3× 210 1.0× 29 1.5k
Graciela Andonegui Canada 20 1.2k 2.4× 588 1.2× 292 0.9× 82 0.3× 317 1.6× 38 2.4k
Yiting Tang China 24 787 1.5× 1.2k 2.4× 313 0.9× 64 0.2× 215 1.1× 50 2.1k
Shunji Hasegawa Japan 27 430 0.8× 268 0.5× 491 1.5× 90 0.3× 340 1.7× 119 1.9k
Wolf‐Dietrich Döcke Germany 22 893 1.7× 233 0.5× 592 1.8× 84 0.3× 80 0.4× 31 1.7k
Kimm J. Hamann United States 24 357 0.7× 447 0.9× 105 0.3× 119 0.4× 212 1.1× 37 1.5k
Christian Herr Germany 29 487 0.9× 583 1.2× 195 0.6× 302 1.1× 645 3.2× 94 2.2k

Countries citing papers authored by Qixing Chen

Since Specialization
Citations

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

Fields of papers citing papers by Qixing Chen

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Qixing Chen

This figure shows the co-authorship network connecting the top 25 collaborators of Qixing Chen. A scholar is included among the top collaborators of Qixing Chen 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 Qixing Chen. Qixing Chen 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.
Shen, Lihua, Zehua Wu, Xiwang Liu, et al.. (2025). Hepcidin sustains Kupffer cell immune defense against bloodstream bacterial infection via gut-derived metabolites in mice. Journal of Clinical Investigation. 135(17).
2.
Huang, Di, et al.. (2024). Advances and challenges of signal readout systems in CRISPR-based biosensors for point-of-care testing of nucleic acid. TrAC Trends in Analytical Chemistry. 178. 117856–117856. 12 indexed citations
3.
Chen, Qixing, et al.. (2024). On the Immersed Boundary Method with Time-Filter-SAV for Solving Fluid–Structure Interaction Problem. Journal of Scientific Computing. 100(2). 1 indexed citations
4.
Chen, Yinghu, Lingfeng Mao, Dengming Lai, et al.. (2023). Improved targeting of the 16S rDNA nanopore sequencing method enables rapid pathogen identification in bacterial pneumonia in children. Frontiers in Cellular and Infection Microbiology. 12. 1001607–1001607. 6 indexed citations
5.
Zhang, Kai, Yang Wang, Yue Jin, et al.. (2023). TREM2hi resident macrophages protect the septic heart by maintaining cardiomyocyte homeostasis. Nature Metabolism. 5(1). 129–146. 115 indexed citations breakdown →
7.
Hou, Jinchao, Qixing Chen, Xiaoliang Wu, et al.. (2017). S1PR3 Signaling Drives Bacterial Killing and Is Required for Survival in Bacterial Sepsis. American Journal of Respiratory and Critical Care Medicine. 196(12). 1559–1570. 45 indexed citations
8.
Chen, Chi, et al.. (2017). TRIM22-Mediated Apoptosis is Associated with Bak Oligomerization in Monocytes. Scientific Reports. 7(1). 39961–39961. 20 indexed citations
9.
Xie, Guohao, Qixing Chen, Baoli Cheng, & Xiangming Fang. (2014). Defensins and Sepsis. BioMed Research International. 2014. 1–5. 17 indexed citations
10.
Chen, Qixing, Yue Jin, Tao Zhu, et al.. (2013). Triggering Receptor Expressed on Myeloid Cells-2 Protects against Polymicrobial Sepsis by Enhancing Bacterial Clearance. American Journal of Respiratory and Critical Care Medicine. 188(2). 201–212. 71 indexed citations
11.
Chen, Qixing, Chi Chen, Xiwang Liu, et al.. (2013). Activation of Triggering Receptor Expressed on Myeloid Cells-1 Protects Monocyte from Apoptosis through Regulation of Myeloid Cell Leukemia-1. Anesthesiology. 118(5). 1140–1149. 11 indexed citations
12.
Zhang, Kai, et al.. (2013). Hepcidin protects sepsis through regulating iron homeostasis to inhibit immunocyte apoptosis in mice (P4435). The Journal of Immunology. 190(Supplement_1). 206.5–206.5. 1 indexed citations
13.
Li, Caixia, Guohao Xie, Baoli Cheng, et al.. (2013). Altered melatonin secretion and circadian gene expression with increased proinflammatory cytokine expression in early-stage sepsis patients. Molecular Medicine Reports. 7(4). 1117–1122. 43 indexed citations
14.
Chen, Qixing, Yuhong Jin, Ning Zhang, et al.. (2012). Circulating nucleosomes as a predictor of sepsis and organ dysfunction in critically ill patients. International Journal of Infectious Diseases. 16(7). e558–e564. 62 indexed citations
15.
Wu, Shuijing, Kai Zhang, Chen Lv, et al.. (2011). Nuclear factor-κB mediated lipopolysaccharide-induced mRNA expression of hepcidin in human peripheral blood leukocytes. Innate Immunity. 18(2). 318–324. 24 indexed citations
16.
17.
Book, Malte, Qixing Chen, Lutz Lehmann, et al.. (2007). Inducibility of the endogenous antibiotic peptide β-defensin 2 is impaired in patients with severe sepsis. Critical Care. 11(1). R19–R19. 25 indexed citations
18.
Shu, Qiang, Xianghong Zhang, Shanshan Shi, et al.. (2006). Interleukin 10.G microsatellite in the promoter region of the interleukin-10 gene in severe sepsis. Chinese Medical Journal. 119(3). 197–201. 5 indexed citations
19.
Shu, Qiang, Zhuo Shi, Zhengyan Zhao, et al.. (2006). PROTECTION AGAINST PSEUDOMONAS AERUGINOSA PNEUMONIA AND SEPSIS-INDUCED LUNG INJURY BY OVEREXPRESSION of β-DEFENSIN-2 IN RATS. Shock. 26(4). 365–371. 39 indexed citations
20.
Chen, Qixing, et al.. (2006). [IL-10 inhibits inducible expression pattern of beta-defensin-2 in human peripheral blood cells].. PubMed. 35(6). 596–9, 604. 1 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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