Shuna Cui

648 citations
26 papers · 466 · h-index 12

Impact in

Papers in

Shuna Cui

24 papers receiving 460 citations

Peers

Shuna Cui
Comparison fields: 5 of 91
  • Complementary and alternative medicine 32
  • Immunology 62
  • Immunology and Allergy 17
  • Pharmacology 25
  • Molecular Biology 188
Replace Ming‐Chang Hsieh with:
Ming‐Chang Hsieh Taiwan
Juan Shen China
I. M. Hussaini Nigeria
Yunju Jeong South Korea
Gabriele Hölzlwimmer Germany
Wenbin Zhao China
Fang‐Yuan Gong China
Ekambaranellore Prakash Taiwan
Feifei Nong China
Ju Yuan China
Shuna Cui relative to Ming‐Chang Hsieh Taiwan Ming‐Chang Hsieh's profile →
Citations per field
00.5×1.5×2.2×
Ming‐Chang Hsieh · 1×
Citations per year

Countries citing papers authored by Shuna Cui

Since Specialization
Citations

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

Fields of papers citing papers by Shuna Cui

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Shuna Cui, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Shuna Cui Line = papers co-authored together Shuna Cui links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 26 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201785
2 201856
3 202353
4 201938
5 201335
6 201031
7 202026
8 202219
9 202318
10 202317
11 202014
12 201612
13 201311
14 202010
15 20239
16 20246
17 20215
18
[Anti-inflammatory effect of Syk inhibitor in LPS stimulated macrophages].
20135
19
[Effect of genistein on the TLR and MAPK transduction cascades in lipopolysaccharide -stimulated macrophages].
20144
20 20253

About Shuna Cui

Shuna Cui is a scholar working on Molecular Biology, Epidemiology, Immunology, Infectious Diseases and Plant Science, having authored 26 papers that have together received 466 indexed citations. Recurring topics across this work include Antifungal resistance and susceptibility (4 papers), Fungal Infections and Studies (4 papers), Natural product bioactivities and synthesis (2 papers), Immune cells in cancer (2 papers), CRISPR and Genetic Engineering (2 papers), Virus-based gene therapy research (2 papers), Endometriosis Research and Treatment (1 paper) and Cryptography and Data Security (1 paper). The work is most often cited by research in Complementary and alternative medicine (32 citations), Immunology (62 citations), Immunology and Allergy (17 citations), Pharmacology (25 citations) and Molecular Biology (188 citations). Shuna Cui has collaborated with scholars based in China, Germany and Egypt. Frequent co-authors include Qingqing Wu, Ursula Bilitewski, Changshui Yang, Juan Wang, Jing Qian, Ping Bo, Shihua Li, Jing Qian, Juan Wang and Shanshan Chen. Their work appears in journals such as International Immunopharmacology, Phytomedicine, Molecules, Nature Communications and Chemico-Biological Interactions.

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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