Zeqing Feng

5.1k total citations · 2 hit papers
17 papers, 2.6k citations indexed

About

Zeqing Feng is a scholar working on Immunology, Infectious Diseases and Molecular Biology. According to data from OpenAlex, Zeqing Feng has authored 17 papers receiving a total of 2.6k indexed citations (citations by other indexed papers that have themselves been cited), including 12 papers in Immunology, 7 papers in Infectious Diseases and 5 papers in Molecular Biology. Recurrent topics in Zeqing Feng's work include SARS-CoV-2 and COVID-19 Research (5 papers), interferon and immune responses (4 papers) and COVID-19 Clinical Research Studies (4 papers). Zeqing Feng is often cited by papers focused on SARS-CoV-2 and COVID-19 Research (5 papers), interferon and immune responses (4 papers) and COVID-19 Clinical Research Studies (4 papers). Zeqing Feng collaborates with scholars based in China and United States. Zeqing Feng's co-authors include Yongwen Chen, Bo Diao, Chenhui Wang, Yuzhang Wu, Yueping Liu, Zilin Yuan, Yingjun Tan, Li Chen, Ying Liu and Xiewan Chen and has published in prestigious journals such as Nature Communications, Clinical Infectious Diseases and Science Advances.

In The Last Decade

Zeqing Feng

15 papers receiving 2.5k citations

Hit Papers

2 papers align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Reduction and Functional Exhaustion of T Cells in Patients With Coronavirus Disease 2019 (COVID-19)

2020 1.7k citations Bo Diao, Chenhui Wang et al. Frontiers in Immunology profile →
Human kidney is a target for novel severe acute respiratory syndrome coronavirus 2 infection

2021 347 citations Bo Diao, Chenhui Wang et al. Nature Communications profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Zeqing Feng China	11	1.8k	948	507	433	299	17	2.6k
Bo Diao China	15	1.9k 1.1×	1.0k 1.1×	456 0.9×	501 1.2×	365 1.2×	41	2.8k
Chenhui Wang China	8	1.8k 1.0×	937 1.0×	372 0.7×	360 0.8×	278 0.9×	13	2.4k
Yueping Liu China	12	1.8k 1.0×	918 1.0×	344 0.7×	488 1.1×	274 0.9×	31	2.5k
Zilin Yuan China	7	1.7k 1.0×	911 1.0×	336 0.7×	315 0.7×	265 0.9×	11	2.2k
Yingjun Tan China	4	1.7k 1.0×	909 1.0×	328 0.6×	297 0.7×	263 0.9×	6	2.2k
Xiewan Chen China	11	1.4k 0.8×	775 0.8×	295 0.6×	419 1.0×	364 1.2×	26	2.1k
Haijing Yu China	9	2.7k 1.5×	1.6k 1.6×	425 0.8×	445 1.0×	425 1.4×	14	3.5k
Hongwu Wang China	14	2.7k 1.5×	1.5k 1.6×	554 1.1×	520 1.2×	423 1.4×	37	3.8k
Zili Zhang China	18	967 0.5×	445 0.5×	630 1.2×	447 1.0×	287 1.0×	49	2.4k

Countries citing papers authored by Zeqing Feng

Since Specialization

Citations

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

Fields of papers citing papers by Zeqing Feng

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Zeqing Feng

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

All Works

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17 of 17 papers shown

Wang, Chenhui, Zeqing Feng, Fei Lei, et al.. (2024). MS4A6D Promotes carrageenan-induced footpad swelling in mice through enhancing macrophages-derived inflammation. Molecular Immunology. 169. 28–36.

Cheng, Shuyuan, et al.. (2024). The impact of the COVID-19 pandemic on the professional commitment of male nursing students in China: a descriptive comparative study. BMC Nursing. 23(1). 771–771.

Li, Sirui, Chenhui Wang, Yue Pan, et al.. (2023). Tetraspan MS4A6D is a coreceptor of MHC class II antigen (MHC-II) that promotes macrophages-derived inflammation. Molecular Immunology. 160. 121–132. 3 indexed citations

Diao, Bo, Chenhui Wang, Rongshuai Wang, et al.. (2021). Human kidney is a target for novel severe acute respiratory syndrome coronavirus 2 infection. Nature Communications. 12(1). 2506–2506. 347 indexed citations breakdown →

Feng, Zeqing, Bo Diao, Chao Tu, et al.. (2021). SARS-CoV-2 Induces Lymphocytopenia by Promoting Inflammation and Decimates Secondary Lymphoid Organs. Frontiers in Immunology. 12. 661052–661052. 61 indexed citations

Wang, Chenhui, Yue Pan, Xiaoyong Huang, et al.. (2020). CD1d1 intrinsic signaling in macrophages controls NLRP3 inflammasome expression during inflammation. Science Advances. 6(43). 39 indexed citations

Diao, Bo, Chenhui Wang, Yingjun Tan, et al.. (2020). Reduction and Functional Exhaustion of T Cells in Patients With Coronavirus Disease 2019 (COVID-19). Frontiers in Immunology. 11. 827–827. 1724 indexed citations breakdown →

Liu, Yueping, Yue Pan, Zhenhong Hu, et al.. (2020). Thymosin Alpha 1 Reduces the Mortality of Severe Coronavirus Disease 2019 by Restoration of Lymphocytopenia and Reversion of Exhausted T Cells. Clinical Infectious Diseases. 71(16). 2150–2157. 102 indexed citations

Feng, Zeqing, Bo Diao, Rongshuai Wang, et al.. (2020). Detection of the SARS-CoV-2 Nucleocaspid Protein (NP) Using Immunohistochemistry. BIO-PROTOCOL. 10(7). 3 indexed citations

10.

Huang, Xiaoyong, Zeqing Feng, Yuanzhong Jiang, et al.. (2019). VSIG4 mediates transcriptional inhibition of Nlrp3 and Il-1 β in macrophages. Science Advances. 5(1). eaau7426–eaau7426. 88 indexed citations

11.

Li, Jialin, Bo Diao, Sheng Guo, et al.. (2017). VSIG4 inhibits proinflammatory macrophage activation by reprogramming mitochondrial pyruvate metabolism. Nature Communications. 8(1). 1322–1322. 125 indexed citations

12.

Jin, Jie, Chaowu Yang, Xiaosong Jiang, et al.. (2017). Molecular characterization, expression, and functional analysis of chicken TRAF6. Genetics and Molecular Research. 16(1). 3 indexed citations

13.

Feng, Zeqing, et al.. (2015). Molecular characterization, tissue distribution and expression analysis of TRIM25 in Gallus gallus domesticus. Gene. 561(1). 138–147. 16 indexed citations

14.

Feng, Zeqing, et al.. (2015). Molecular cloning and expression analysis of TRAF3 in chicken. Genetics and Molecular Research. 14(2). 4408–4419. 20 indexed citations

15.

Liu, Xianqing, Fei Wang, Jie Jin, et al.. (2015). MyD88Polymorphisms and Association with Susceptibility to Salmonella Pullorum. BioMed Research International. 2015. 1–7. 16 indexed citations

16.

Feng, Zeqing, et al.. (2013). Expression Pattern of Genes of RLR-Mediated Antiviral Pathway in Different-Breed Chicken Response to Marek’s Disease Virus Infection. BioMed Research International. 2013. 1–9. 10 indexed citations

17.

H, Lu, Jiehui Li, Li Y, et al.. (2003). [Primary investigation on the changing mode of plasma specific IgG antibody in SARS patients and their physicians and nurses].. PubMed. 35 Suppl. 23–5. 7 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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