Mei-Juan Shi

888 total citations · 1 hit paper
6 papers, 611 citations indexed

About

Mei-Juan Shi is a scholar working on Molecular Biology, Immunology and Allergy and Immunology. According to data from OpenAlex, Mei-Juan Shi has authored 6 papers receiving a total of 611 indexed citations (citations by other indexed papers that have themselves been cited), including 4 papers in Molecular Biology, 2 papers in Immunology and Allergy and 2 papers in Immunology. Recurrent topics in Mei-Juan Shi's work include Cell Adhesion Molecules Research (2 papers), S100 Proteins and Annexins (2 papers) and Neutrophil, Myeloperoxidase and Oxidative Mechanisms (2 papers). Mei-Juan Shi is often cited by papers focused on Cell Adhesion Molecules Research (2 papers), S100 Proteins and Annexins (2 papers) and Neutrophil, Myeloperoxidase and Oxidative Mechanisms (2 papers). Mei-Juan Shi collaborates with scholars based in China and United States. Mei-Juan Shi's co-authors include Yongliang Cao, Lijing Kang, Wenying Fan, Xing Yang, Bing–Qiao Zhao, Huilin Yu, Ranran Wang, Yuanbo Zhu, Xiaofei Bai and Haiyu Luo and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Nature Communications and Blood.

In The Last Decade

Mei-Juan Shi

6 papers receiving 608 citations

Hit 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.

Neutrophil extracellular traps released by neutrophils impair revascularization and vascular remodeling after stroke

2020 351 citations Lijing Kang, Huilin Yu 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
Mei-Juan Shi China	6	318	273	248	86	72	6	611
Haiyu Luo China	9	232 0.7×	221 0.8×	224 0.9×	105 1.2×	103 1.4×	11	578
David A. Giles United States	10	342 1.1×	143 0.5×	183 0.7×	43 0.5×	83 1.2×	13	630
Alexandre Paré Canada	8	296 0.9×	201 0.7×	194 0.8×	35 0.4×	36 0.5×	9	674
Sarah Floris Netherlands	11	282 0.9×	244 0.9×	293 1.2×	48 0.6×	71 1.0×	11	835
Florian Ingelfinger Switzerland	10	364 1.1×	135 0.5×	288 1.2×	31 0.4×	54 0.8×	18	656
Jolien Wolbert Germany	10	298 0.9×	193 0.7×	243 1.0×	42 0.5×	123 1.7×	10	680
Albert Caramoy Germany	19	115 0.4×	307 1.1×	238 1.0×	39 0.5×	69 1.0×	35	1.1k
Stefaniya Boneva Germany	16	190 0.6×	221 0.8×	214 0.9×	24 0.3×	95 1.3×	44	820
Mason A. Brown United States	6	122 0.4×	118 0.4×	186 0.8×	74 0.9×	106 1.5×	10	446
Matthias Vockel Germany	9	161 0.5×	388 1.4×	105 0.4×	50 0.6×	23 0.3×	10	673

Countries citing papers authored by Mei-Juan Shi

Since Specialization

Citations

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

Fields of papers citing papers by Mei-Juan Shi

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Mei-Juan Shi

This figure shows the co-authorship network connecting the top 25 collaborators of Mei-Juan Shi. A scholar is included among the top collaborators of Mei-Juan Shi 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 Mei-Juan Shi. Mei-Juan Shi 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:

6 of 6 papers shown

1.

Li, Mengmeng, et al.. (2024). LncRNA KCNQ1OT1 promotes NLRP3 inflammasome activation in Parkinson's disease by regulating pri-miR-186/mature miR-186/NLRP3 axis. Biochimica et Biophysica Acta (BBA) - Molecular Basis of Disease. 1870(8). 167454–167454. 5 indexed citations

2.

Yu, Huilin, Haiyu Luo, Shisheng Wang, et al.. (2022). The NEDD8-activating enzyme inhibitor MLN4924 reduces ischemic brain injury in mice. Proceedings of the National Academy of Sciences. 119(6). 45 indexed citations

3.

Wang, Ranran, Yuanbo Zhu, Zhongwang Liu, et al.. (2021). Neutrophil extracellular traps promote tPA-induced brain hemorrhage via cGAS in mice with stroke. Blood. 138(1). 91–103. 158 indexed citations

4.

Kang, Lijing, Huilin Yu, Xing Yang, et al.. (2020). Neutrophil extracellular traps released by neutrophils impair revascularization and vascular remodeling after stroke. Nature Communications. 11(1). 2488–2488. 351 indexed citations breakdown →

5.

Lu, Lu, Xiaofei Bai, Yongliang Cao, et al.. (2018). Growth Differentiation Factor 11 Promotes Neurovascular Recovery After Stroke in Mice. Frontiers in Cellular Neuroscience. 12. 205–205. 44 indexed citations

6.

Shi, Mei-Juan, et al.. (1994). Analysis of twin ferrite toroidal phase shifter in grooved waveguide. IEEE Transactions on Microwave Theory and Techniques. 42(4). 616–621. 8 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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