Jun Wei
Impact in
- Genetics top 0.5%
- Glioma Diagnosis and Treatment
- Immunology top 1%
- Immune cells in cancer
- Immunotherapy and Immune Responses
- Immune Cell Function and Interaction
Papers in
- Immunology 19
- Immune cells in cancer 12
- Immune Cell Function and Interaction 7
- Immunotherapy and Immune Responses 5
- Genetics 10
- Glioma Diagnosis and Treatment 10
- Co-authors
- Amy B. Heimberger (40 shared papers)Ling-Yuan Kong (19 shared papers)Waldemar Priebe (13 shared papers)Wei Qiao (13 shared papers)Gregory N. Fuller (20 shared papers)Adam Wu (5 shared papers)Yongtao Wang (7 shared papers)Raymond A. Sawaya (8 shared papers)
- Journals
- Neuro-Oncology (9 papers)Clinical Cancer Research (8 papers)OncoImmunology (4 papers)Journal of Clinical Investigation (3 papers)Journal of Neuro-Oncology (2 papers)
- Partner nations
- United StatesChinaAustralia
In The Last Decade
Jun Wei
53 papers receiving 5.5k citations
Jun Wei's Hit Papers
Peers
Comparison fields: 5 of 94
- Genetics 1.6k
- Immunology 2.6k
- Oncology 2.0k
- Neurology 630
- Cancer Research 1.0k
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 53 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2010 | 569 | |
| 2 | PD-L1 expression and prognostic impact in glioblastoma Hit paper breakdown → | 2015 | 507 |
| 3 | 2016 | 376 | |
| 4 | 2018 | 324 | |
| 5 | 2017 | 276 | |
| 6 | 2010 | 243 | |
| 7 | 2013 | 230 | |
| 8 | 2021 | 214 | |
| 9 | 2007 | 208 | |
| 10 | 2011 | 195 | |
| 11 | 2013 | 186 | |
| 12 | 2013 | 178 | |
| 13 | 2015 | 176 | |
| 14 | 2008 | 163 | |
| 15 | 2019 | 160 | |
| 16 | 2011 | 122 | |
| 17 | 2020 | 121 | |
| 18 | 2014 | 116 | |
| 19 | 2021 | 115 | |
| 20 | 2008 | 113 |
About Jun Wei
Jun Wei is a scholar working on Immunology, Genetics, Cancer Research, Oncology and Neurology, having authored 53 papers that have together received 5.6k indexed citations. Recurring topics across this work include Immune cells in cancer (12 papers), Glioma Diagnosis and Treatment (10 papers), MicroRNA in disease regulation (10 papers), Cytokine Signaling Pathways and Interactions (8 papers), Immune Cell Function and Interaction (7 papers), Neuroinflammation and Neurodegeneration Mechanisms (6 papers), Cancer Immunotherapy and Biomarkers (5 papers) and Immunotherapy and Immune Responses (5 papers). The work is most often cited by research in Genetics (1.6k citations), Immunology (2.6k citations), Oncology (2.0k citations), Neurology (630 citations) and Cancer Research (1.0k citations). Jun Wei has collaborated with scholars based in United States, China and Australia. Frequent co-authors include Amy B. Heimberger, Ling-Yuan Kong, Waldemar Priebe, Wei Qiao, Gregory N. Fuller, Adam Wu, Yongtao Wang, Raymond A. Sawaya, Konrad R. Gabrusiewicz and Ganesh Rao. Their work appears in journals such as Neuro-Oncology, Clinical Cancer Research, OncoImmunology, Journal of Clinical Investigation and Journal of Neuro-Oncology.
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.