Kun Yang

7.2k citations
82 papers · 3.6k indexed · 2 hit papers · h-index 27

Impact in

  • Immunology top 1%
    • interferon and immune responses
    • Immune Response and Inflammation
    • Immunodeficiency and Autoimmune Disorders
    • Immune Cell Function and Interaction
    • Viral Infections and Vectors

Papers in

Kun Yang

79 papers receiving 3.6k citations

Hit Papers

Tonic prime-boost of STING signalling mediates Niemann–Pick disease type C 2021 · 160 citations
1602003202620102018100200300400500

Peers

Kun Yang
Comparison fields: 5 of 114
  • Immunology 2.0k
  • Infectious Diseases 802
  • Epidemiology 1.0k
  • Cancer Research 403
  • Molecular Biology 1.2k
Replace Salman T. Qureshi with:
Salman T. Qureshi Canada
Jonathan P. Moorman United States
Ulrich A. Maus Germany
Theo S. Plantinga Netherlands
Kenji Fukudome Japan
Hiromitsu Hara Japan
Volkan Özenci Sweden
Shuye Zhang China
Sanna M. Goyert United States
Samithamby Jeyaseelan United States
Kun Yang relative to Salman T. Qureshi Canada Salman T. Qureshi's profile →
Citations per field
00.5×3.3×
Salman T. Qureshi · 1×
Citations per year

Countries citing papers authored by Kun Yang

Since Specialization
Citations

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

Fields of papers citing papers by Kun Yang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

The 25 scholars most cited alongside Kun Yang, 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 Kun Yang Line = papers co-authored together Kun Yang links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 20255
2 20251
3 20244
4 20242
5 20242
6 202328
7 202238
8 202211
9 20208
10 2020248
11 20192
12 201720
13 201637
14 201517
15 201413
16 20088
17 2008238
18 2007110
19 200645
20 20035

About Kun Yang

Kun Yang is a scholar working on Immunology, Critical Care and Intensive Care Medicine, Cancer Research, Pharmacology and Neurology, having authored 82 papers that have together received 3.6k indexed citations. Recurring topics across this work include interferon and immune responses (21 papers), Immune Response and Inflammation (14 papers), RNA regulation and disease (8 papers), Viral Infections and Vectors (6 papers), Alkaloids: synthesis and pharmacology (6 papers), MicroRNA in disease regulation (6 papers), Pharmacological Effects of Natural Compounds (5 papers) and Mosquito-borne diseases and control (5 papers). The work is most often cited by research in Immunology (2.0k citations), Infectious Diseases (802 citations), Epidemiology (1.0k citations), Cancer Research (403 citations) and Molecular Biology (1.2k citations). Kun Yang has collaborated with scholars based in China, United States and France. Frequent co-authors include Nan Yan, Jianjun Wu, Nicole Dobbs, Jean‐Laurent Casanova, Emmanuelle Jouanguy, Stéphanie Boisson‐Dupuis, Anne Puel, Ariane Chapgier, Capucine Pïcard and Xi Huang. Their work appears in journals such as Scientific Reports, The Journal of Experimental Medicine, Immunological Reviews, Critical Care Medicine and Clinical Infectious Diseases.

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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2026