Wei Yan

3.8k citations
91 papers · 2.8k indexed · h-index 30

Impact in

  • Immunology top 5%
    • Neutrophil, Myeloperoxidase and Oxidative Mechanisms
    • Immune Response and Inflammation
    • Immune cells in cancer
    • Cancer-related molecular mechanisms research

Papers in

Wei Yan

85 papers receiving 2.8k citations

Peers

Wei Yan
Comparison fields: 5 of 119
  • Immunology 803
  • Cancer Research 471
  • Hepatology 224
  • Clinical Biochemistry 181
  • Aging 43
Replace Maja T. Lindenmeyer with:
Maja T. Lindenmeyer Germany
Wataru Kamiike Japan
Lorenza Tacchini Italy
Craig R. Brooks United States
Juan M. Cárcamo United States
Taro Sakamoto Japan
Pothana Saikumar United States
Bin Yi China
Weifeng Shen China
Yoshitsugu Takabatake Japan
Wei Yan relative to Maja T. Lindenmeyer Germany Maja T. Lindenmeyer's profile →
Citations per field
00.5×4.6×
Maja T. Lindenmeyer · 1×
Citations per year

Countries citing papers authored by Wei Yan

Since Specialization
Citations

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

Fields of papers citing papers by Wei Yan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown
#Work
1 20250
2 20242
3 202411
4 20241
5 20238
6 202322
7 202271
8 20228
9 202130
10 202087
11 202047
12 20198
13 20194
14 201829
15 201210
16 2011288
17 200825
18 200811
19 200859
20
[Hfgl2/fibroleukin expression in liver and peripheral blood mononuclear cells (PBMC) and its correlation with disease severity].
20042

About Wei Yan

Wei Yan is a scholar working on Aging, Hepatology, Cancer Research, Immunology and Molecular Biology, having authored 91 papers that have together received 2.8k indexed citations. Recurring topics across this work include Liver Disease Diagnosis and Treatment (9 papers), Reproductive Biology and Fertility (9 papers), Liver Diseases and Immunity (7 papers), RNA modifications and cancer (6 papers), Inflammasome and immune disorders (6 papers), Immune Response and Inflammation (6 papers), Hepatitis B Virus Studies (5 papers) and Axon Guidance and Neuronal Signaling (5 papers). The work is most often cited by research in Immunology (803 citations), Cancer Research (471 citations), Hepatology (224 citations), Clinical Biochemistry (181 citations) and Aging (43 citations). Wei Yan has collaborated with scholars based in China, United States and Saudi Arabia. Frequent co-authors include Dean Tian, Allan Tsung, Yu Fu, Hai Huang, Ping Han, Mei Liu, Su Zhou, Michael T. Lotze, John Evankovich and Charles T. Esmon. Their work appears in journals such as Frontiers in Immunology, Hepatology, International Immunopharmacology, PLoS ONE and Journal of Cellular Physiology.

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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