Kun Mei

543 total citations
38 papers, 366 citations indexed

About

Kun Mei is a scholar working on Molecular Biology, Epidemiology and Genetics. According to data from OpenAlex, Kun Mei has authored 38 papers receiving a total of 366 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Molecular Biology, 9 papers in Epidemiology and 9 papers in Genetics. Recurrent topics in Kun Mei's work include Viral gastroenteritis research and epidemiology (7 papers), Influenza Virus Research Studies (6 papers) and Virus-based gene therapy research (4 papers). Kun Mei is often cited by papers focused on Viral gastroenteritis research and epidemiology (7 papers), Influenza Virus Research Studies (6 papers) and Virus-based gene therapy research (4 papers). Kun Mei collaborates with scholars based in China, United Kingdom and United States. Kun Mei's co-authors include Rong Yang, Xiaolan Yu, Quanjiao Chen, Zhimin Gao, Lihua Zhao, Di Liu, Jianjun Chen, Yuhai Bi, Weifeng Shi and George F. Gao and has published in prestigious journals such as The Lancet, Bioresource Technology and Frontiers in Microbiology.

In The Last Decade

Kun Mei

34 papers receiving 355 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Kun Mei China	11	131	119	110	96	82	38	366
Sanjay Mukherjee India	13	129 1.0×	92 0.8×	52 0.5×	31 0.3×	24 0.3×	31	373
Liangyan Zhang China	11	51 0.4×	84 0.7×	84 0.8×	20 0.2×	22 0.3×	33	278
Karola Obojes Germany	7	82 0.6×	252 2.1×	102 0.9×	38 0.4×	42 0.5×	7	429
Yinli Xie China	10	54 0.4×	44 0.4×	76 0.7×	36 0.4×	89 1.1×	16	287
И. Л. Кузнецова Russia	11	136 1.0×	61 0.5×	39 0.4×	81 0.8×	11 0.1×	28	298
Elise Larson United States	6	128 1.0×	36 0.3×	92 0.8×	25 0.3×	42 0.5×	6	274
Tomohiko Ogasawara Japan	6	37 0.3×	147 1.2×	42 0.4×	65 0.7×	15 0.2×	23	244
Kirsten E. McLoughlin Ireland	7	163 1.2×	96 0.8×	92 0.8×	23 0.2×	21 0.3×	7	314
Coralie Guy Ireland	7	140 1.1×	78 0.7×	135 1.2×	22 0.2×	10 0.1×	8	378
Michelle L. Pleet United States	11	304 2.3×	84 0.7×	165 1.5×	13 0.1×	32 0.4×	24	478

Countries citing papers authored by Kun Mei

Since Specialization

Citations

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

Fields of papers citing papers by Kun Mei

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Kun Mei

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

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

Ding, Minling, Kun Mei, Xuanzhao Lu, et al.. (2025). Multi-target nanocomposites for Alzheimer’s treatment via microenvironment modulation and β-amyloid plaque clearance. Journal of Material Science and Technology. 248. 281–294. 2 indexed citations

Hu, Jun, Peiyao Yang, Kun Mei, et al.. (2024). Biodegradation of 3-methylpyridine by an isolated strain, Gordonia rubripertincta ZJJ. Bioresource Technology. 412. 131303–131303. 1 indexed citations

Yang, Qian, Minling Ding, Xin Wang, et al.. (2024). Blood-brain barrier permeable carbon nano-assemblies for amyloid-β clearance and neurotoxic attenuation. Colloids and Surfaces B Biointerfaces. 244. 114182–114182. 7 indexed citations

Liu, Yang, Tsai‐Hung Fan, Kun Mei, & Liming Zhou. (2024). PG-YOLO: A Lightweight Vehicle Detection Method for Drones. 1492–1497.

Li, Yuze, et al.. (2024). Isolation and identification of a novel goose-origin reovirus GD218 and its pathogenicity experiments. Frontiers in Veterinary Science. 11. 1423122–1423122. 1 indexed citations

Wang, Yiqiao, et al.. (2024). Research progress of porcine epidemic diarrhea virus S protein. Frontiers in Microbiology. 15. 1396894–1396894. 20 indexed citations

Zhang, Wandi, Meihong Wang, Sheng Yuan, et al.. (2023). Characterization and pathogenicity evaluation of recombinant novel duck reovirus isolated from Southeast China. Frontiers in Veterinary Science. 10. 1124999–1124999. 12 indexed citations

Shao, Xu, Minling Ding, Kun Mei, et al.. (2023). Photooxidative inhibition and decomposition of β-amyloid in Alzheimer's by nano-assemblies of transferrin and indocyanine green. International Journal of Biological Macromolecules. 241. 124432–124432. 12 indexed citations

Mei, Kun, et al.. (2023). Construction and validation of a nomogram based on the log odds of positive lymph nodes to predict cancer-specific survival in patients with small cell lung cancer after surgery. Heliyon. 9(8). e18502–e18502. 7 indexed citations

10.

Chen, Gang, et al.. (2023). Machine learning-based prediction model and visual interpretation for prostate cancer. BMC Urology. 23(1). 164–164. 6 indexed citations

11.

Zhang, Xinyu, Gaojie Chen, Jinyue Guo, et al.. (2023). Identification, pathological, and genomic characterization of novel goose reovirus associated with liver necrosis in geese, China. Poultry Science. 103(2). 103269–103269. 6 indexed citations

12.

Li, Zhili, Wandi Zhang, Liangliang Ma, et al.. (2022). Difference analysis of intestinal microbiota and metabolites in piglets of different breeds exposed to porcine epidemic diarrhea virus infection. Frontiers in Microbiology. 13. 990642–990642. 8 indexed citations

13.

Cui, Jin, Lan Cao, Siyu Wu, et al.. (2017). Phylogeny, Pathogenicity, and Transmission of H5N1 Avian Influenza Viruses in Chickens. Frontiers in Cellular and Infection Microbiology. 7. 328–328. 9 indexed citations

14.

Wang, Fei, Quanjiao Chen, Shanshan Li, et al.. (2017). Linear DNA vaccine prepared by large-scale PCR provides protective immunity against H1N1 influenza virus infection in mice. Veterinary Microbiology. 205. 124–130. 2 indexed citations

15.

Jia, Yun, et al.. (2015). Multistep microsatellite mutation leading to father–child mismatch of FGA locus in a case of non-exclusion parentage. Legal Medicine. 17(5). 364–365. 4 indexed citations

16.

Mei, Kun, Guang Liu, Zhenzhen Chen, et al.. (2015). Deep sequencing reveals the viral adaptation process of environment-derived H10N8 in mice. Infection Genetics and Evolution. 37. 8–13. 15 indexed citations

17.

Mei, Kun, et al.. (2014). Isolation and identification of age-related DNA methylation markers for forensic age-prediction. Forensic Science International Genetics. 11. 117–125. 46 indexed citations

18.

Huang, Daixin, et al.. (2010). Typing of 24 mtDNA SNPs in a Chinese population using SNaPshot minisequencing. Journal of Huazhong University of Science and Technology [Medical Sciences]. 30(3). 291–298. 11 indexed citations

19.

Huang, Daixin, et al.. (2004). Study on the application of parent-of-origin specific DNA methylation markers to forensic genetics. Forensic Science International. 154(2-3). 122–127. 13 indexed citations

20.

Mei, Kun, et al.. (1982). An Uncommon Endoscopic Finding: Bleeding Secondary Aortoenteric Fistula. Endoscopy. 14(5). 185–186. 5 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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