Pan Shen

1.8k citations
59 papers · 1.3k · h-index 19

Impact in

Papers in

    • Inflammasome and immune disorders 3
    • Metabolomics and Mass Spectrometry Studies 2
    • Cytokine Signaling Pathways and Interactions 6

Pan Shen

56 papers receiving 1.3k citations

Peers

Pan Shen
Comparison fields: 5 of 103
  • Geriatrics and Gerontology 55
  • Pharmacology 100
  • Immunology 227
  • Rheumatology 151
  • Complementary and alternative medicine 77
Replace Dae‐Myung Jue with:
Dae‐Myung Jue South Korea
Tae‐Hwe Heo South Korea
Aranka Brockmueller Germany
Jeong Ho Seok South Korea
Xin Ba China
Rui Ge China
Xiaofei Zhu China
Bo Kyung Kim South Korea
Hongshan Chen China
Pan Shen relative to Dae‐Myung Jue South Korea Dae‐Myung Jue's profile →
Citations per field
00.5×10×15×18×
Dae‐Myung Jue · 1×
Citations per year

Countries citing papers authored by Pan Shen

Since Specialization
Citations

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

Fields of papers citing papers by Pan Shen

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 59 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2017221
2 2021179
3 2021124
4 202170
5 202168
6 202167
7 202243
8 202341
9 202130
10 201925
11 202024
12 202123
13 202123
14 201722
15 202021
16 202319
17 202019
18 201919
19 202418
20 202118

About Pan Shen

Pan Shen is a scholar working on Molecular Biology, Oncology, Rheumatology, Immunology and Epidemiology, having authored 59 papers that have together received 1.3k indexed citations. Recurring topics across this work include Rheumatoid Arthritis Research and Therapies (8 papers), Cytokine Signaling Pathways and Interactions (6 papers), Natural Compounds in Disease Treatment (3 papers), Inflammasome and immune disorders (3 papers), Immune Cell Function and Interaction (3 papers), Pharmacological Effects of Natural Compounds (3 papers), interferon and immune responses (2 papers) and Metabolomics and Mass Spectrometry Studies (2 papers). The work is most often cited by research in Geriatrics and Gerontology (55 citations), Pharmacology (100 citations), Immunology (227 citations), Rheumatology (151 citations) and Complementary and alternative medicine (77 citations). Pan Shen has collaborated with scholars based in China, United States and Germany. Frequent co-authors include Shenghao Tu, Ying Huang, Xin Ba, Kai Qin, Weiji Lin, Liang Han, Yao Huang, Xuan Deng, Zhe Chen and Zhe Chen. Their work appears in journals such as Journal of Ethnopharmacology, Frontiers in Immunology, Evidence-based Complementary and Alternative Medicine, Frontiers in Pharmacology and Phytomedicine.

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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