Jun Wei
Impact in
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- Systemic Sclerosis and Related Diseases
- Dermatology top 1%
- Dermatologic Treatments and Research
Papers in
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- Systemic Sclerosis and Related Diseases 19
- Trigeminal Neuralgia and Treatments 2
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- Dermatologic Treatments and Research 3
- Co-authors
- John Varga (19 shared papers)Swati Bhattacharyya (10 shared papers)Warren G. Tourtellotte (7 shared papers)Roberta Gonçalves Marangoni (8 shared papers)Michael L. Whitfield (4 shared papers)Monique Hinchcliff (6 shared papers)Feng Fang (7 shared papers)Kazuhiro Komura (3 shared papers)
- Journals
- Arthritis & Rheumatology (4 papers)Arthritis Research & Therapy (2 papers)Oncotarget (2 papers)PLoS ONE (2 papers)American Journal Of Pathology (2 papers)
- Partner nations
- United StatesChinaJapan
In The Last Decade
Jun Wei
33 papers receiving 2.4k citations
Peers
Comparison fields: 5 of 91
- Pathology and Forensic Medicine 1.0k
- Dermatology 380
- Rehabilitation 106
- Immunology 336
- Geriatrics and Gerontology 52
Countries citing papers authored by Jun Wei
This map shows the geographic impact of Jun Wei'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 Wei with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jun Wei more than expected).
Fields of papers citing papers by Jun Wei
This network shows the impact of papers produced by Jun Wei. 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 Wei. The network helps show where Jun Wei may publish in the future.
Co-authors
The 25 scholars most cited alongside Jun Wei, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 33 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2011 | 323 | |
| 2 | 2014 | 277 | |
| 3 | 2011 | 184 | |
| 4 | 2010 | 170 | |
| 5 | 2010 | 150 | |
| 6 | 2012 | 99 | |
| 7 | 2013 | 97 | |
| 8 | 2016 | 96 | |
| 9 | 2015 | 83 | |
| 10 | 2012 | 83 | |
| 11 | 2017 | 77 | |
| 12 | 2011 | 77 | |
| 13 | 2019 | 76 | |
| 14 | 2010 | 71 | |
| 15 | 2013 | 63 | |
| 16 | 2016 | 58 | |
| 17 | 2013 | 53 | |
| 18 | 2020 | 53 | |
| 19 | 2007 | 51 | |
| 20 | 2012 | 37 |
About Jun Wei
Jun Wei is a scholar working on Pathology and Forensic Medicine, Dermatology, Cell Biology, Geriatrics and Gerontology and Molecular Biology, having authored 33 papers that have together received 2.4k indexed citations. Recurring topics across this work include Systemic Sclerosis and Related Diseases (19 papers), Skin and Cellular Biology Research (5 papers), Connective Tissue Growth Factor Research (4 papers), Wnt/β-catenin signaling in development and cancer (4 papers), Dermatologic Treatments and Research (3 papers), Kruppel-like factors research (3 papers), Dermatological and Skeletal Disorders (3 papers) and Trigeminal Neuralgia and Treatments (2 papers). The work is most often cited by research in Pathology and Forensic Medicine (1.0k citations), Dermatology (380 citations), Rehabilitation (106 citations), Immunology (336 citations) and Geriatrics and Gerontology (52 citations). Jun Wei has collaborated with scholars based in United States, China and Japan. Frequent co-authors include John Varga, Swati Bhattacharyya, Warren G. Tourtellotte, Roberta Gonçalves Marangoni, Michael L. Whitfield, Monique Hinchcliff, Feng Fang, Kazuhiro Komura, John Varga and Benjamin D. Korman. Their work appears in journals such as Arthritis & Rheumatology, Arthritis Research & Therapy, Oncotarget, PLoS ONE and American Journal Of Pathology.
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.