Jun Gui

1.5k citations
23 papers · 784 · h-index 15

Impact in

  • Immunology top 10%
    • Immune cells in cancer
    • Immune Cell Function and Interaction
    • interferon and immune responses
    • Immunotherapy and Immune Responses
  • Oncology top 10%
    • Cancer Immunotherapy and Biomarkers

Papers in

    • Immune Cell Function and Interaction 6
    • interferon and immune responses 5
    • Immunotherapy and Immune Responses 4
    • Immune cells in cancer 4
    • Cancer Immunotherapy and Biomarkers 4

Jun Gui

22 papers receiving 780 citations

Peers

Jun Gui
Comparison fields: 5 of 80
  • Immunology 394
  • Oncology 281
  • Cancer Research 83
  • Cell Biology 63
  • Cardiology and Cardiovascular Medicine 84
Replace Mathieu Derouet with:
Mathieu Derouet Canada
Karine Enesa United Kingdom
Evangelos Giampazolias United Kingdom
Shi‐Wei Huang Taiwan
Shan Huang China
Emma M. Carrington Australia
Wai Gin Fong Canada
Xiang-Min Yang China
Takashi Kagari Japan
Céline Colacios France
Jun Gui relative to Mathieu Derouet Canada Mathieu Derouet's profile →
Citations per field
00.5×5.4×
Mathieu Derouet · 1×
Citations per year

Countries citing papers authored by Jun Gui

Since Specialization
Citations

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

Fields of papers citing papers by Jun Gui

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 23 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2017173
2 201884
3 202171
4 201258
5 202448
6 201548
7 202447
8 202143
9 201628
10 201026
11 201125
12 202223
13 201923
14 201522
15 202019
16 202210
17 201910
18 20177
19 20236
20 20245

About Jun Gui

Jun Gui is a scholar working on Immunology, Oncology, Molecular Biology, Cardiology and Cardiovascular Medicine and Cancer Research, having authored 23 papers that have together received 784 indexed citations. Recurring topics across this work include Immune Cell Function and Interaction (6 papers), interferon and immune responses (5 papers), Viral Infections and Immunology Research (4 papers), Cancer Immunotherapy and Biomarkers (4 papers), Immunotherapy and Immune Responses (4 papers), Immune cells in cancer (4 papers), Chronic Lymphocytic Leukemia Research (2 papers) and Endoplasmic Reticulum Stress and Disease (2 papers). The work is most often cited by research in Immunology (394 citations), Oncology (281 citations), Cancer Research (83 citations), Cell Biology (63 citations) and Cardiology and Cardiovascular Medicine (84 citations). Jun Gui has collaborated with scholars based in China, United States and Malaysia. Frequent co-authors include Sidong Xiong, Serge Y. Fuchs, Yue Yan, Kanstantsin V. Katlinski, Wei Xu, Ruizhen Chen, Constantinos Koumenis, J. Alan Diehl, Hallgeir Rui and Ellen Puré. Their work appears in journals such as Nature Communications, Advanced Science, Cancer Immunology Research, PLoS ONE and Cell Metabolism.

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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