Jun Yan

4.0k citations
79 papers · 3.4k · h-index 27

Impact in

  • Neurology top 5%
    • Neuroinflammation and Neurodegeneration Mechanisms
    • Cellular transport and secretion

Papers in

    • Protein Kinase Regulation and GTPase Signaling 7
    • Cancer-related Molecular Pathways 5
    • Cytokine Signaling Pathways and Interactions 4

Jun Yan

77 papers receiving 3.3k citations

Peers

Jun Yan
Comparison fields: 5 of 134
  • Neurology 260
  • Cell Biology 440
  • Molecular Biology 1.8k
  • Biochemistry 119
  • Immunology 397
Replace Sun Sik Bae with:
Sun Sik Bae South Korea
Rivka Ofir Israel
Mireia Niso‐Santano Spain
Razvan Lapadat United States
Dong Ju Son South Korea
Byong Chul Yoo South Korea
Anna Maria Mileo Italy
Fred L. Robinson United States
Daniela De Zio Denmark
Rosa A. González‐Polo Spain
Jun Yan relative to Sun Sik Bae South Korea Sun Sik Bae's profile →
Citations per field
00.5×1.5×
Sun Sik Bae · 1×
Citations per year

Countries citing papers authored by Jun Yan

Since Specialization
Citations

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

Fields of papers citing papers by Jun Yan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 79 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2001461
2 2004449
3 1998399
4 2006160
5 2010126
6 1998120
7 200896
8 199796
9 201688
10 200883
11
Nature of G1/S cell cycle checkpoint defect in ataxia-telangiectasia.
199581
12 200277
13 201276
14 201475
15 201671
16 200962
17 201661
18 200958
19 201158
20 201554

About Jun Yan

Jun Yan is a scholar working on Molecular Biology, Oncology, Cancer Research, Pathology and Forensic Medicine and Neurology, having authored 79 papers that have together received 3.4k indexed citations. Recurring topics across this work include Neuroinflammation and Neurodegeneration Mechanisms (8 papers), Protein Kinase Regulation and GTPase Signaling (7 papers), Probability and Risk Models (5 papers), Cancer-related Molecular Pathways (5 papers), Stochastic processes and financial applications (5 papers), Cytokine Signaling Pathways and Interactions (4 papers), Traditional Chinese Medicine Analysis (4 papers) and Air Quality and Health Impacts (4 papers). The work is most often cited by research in Neurology (260 citations), Cell Biology (440 citations), Molecular Biology (1.8k citations), Biochemistry (119 citations) and Immunology (397 citations). Jun Yan has collaborated with scholars based in China, Australia and Hong Kong. Frequent co-authors include John F. Hancock, Yi‐Zhong Cai, Judith M. Greer, Annette Lane, Sandrine Roy, Ann Apolloni, Judith C. Sluimer, Qiong Luo, Harold Corke and Mei Sun. Their work appears in journals such as Journal of Neuroimmunology, Journal of Biological Chemistry, Biochemical and Biophysical Research Communications, Life Sciences and Molecular and Cellular Biochemistry.

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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