Pin Wang
Impact in
- Immunology top 1%
- Immunotherapy and Immune Responses
- Immune Cell Function and Interaction
- Oncology top 1%
- CAR-T cell therapy research
Papers in
-
- RNA Interference and Gene Delivery 33
- Advanced biosensing and bioanalysis techniques 10
- Oncology 49
- CAR-T cell therapy research 41
- Co-authors
- Kye‐Il Joo (26 shared papers)Yarong Liu (37 shared papers)Li Lin (5 shared papers)Xuetao Cao (4 shared papers)Biliang Hu (14 shared papers)Jin Hou (3 shared papers)Xingguang Liu (2 shared papers)Feng Ma (2 shared papers)
- Journals
- Human Gene Therapy (8 papers)Molecular Therapy (7 papers)The Journal of Immunology (5 papers)PLoS ONE (5 papers)Nature Communications (5 papers)
- Partner nations
- United StatesChinaSouth Korea
In The Last Decade
Pin Wang
141 papers receiving 6.3k citations
Pin Wang's Hit Papers
Peers
Comparison fields: 5 of 135
- Immunology 1.8k
- Oncology 2.0k
- Cancer Research 836
- Biomaterials 800
- Molecular Biology 2.9k
Countries citing papers authored by Pin Wang
This map shows the geographic impact of Pin Wang'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 Pin Wang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Pin Wang more than expected).
Fields of papers citing papers by Pin Wang
This network shows the impact of papers produced by Pin Wang. 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 Pin Wang. The network helps show where Pin Wang may publish in the future.
Co-authors
The 25 scholars most cited alongside Pin Wang, 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 145 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | MicroRNA-146a Feedback Inhibits RIG-I-Dependent Type I IFN Production in Macrophages by Targeting TRAF6, IRAK1, and IRAK2 Hit paper breakdown → | 2009 | 666 |
| 2 | 2010 | 369 | |
| 3 | 2017 | 261 | |
| 4 | 2018 | 173 | |
| 5 | 2008 | 171 | |
| 6 | 2011 | 163 | |
| 7 | 2014 | 157 | |
| 8 | 2018 | 147 | |
| 9 | 2006 | 135 | |
| 10 | 2009 | 135 | |
| 11 | 1994 | 124 | |
| 12 | 2008 | 120 | |
| 13 | 2012 | 119 | |
| 14 | 2014 | 113 | |
| 15 | 2008 | 113 | |
| 16 | 2015 | 102 | |
| 17 | 2013 | 100 | |
| 18 | 2011 | 98 | |
| 19 | 2014 | 98 | |
| 20 | 2017 | 97 |
About Pin Wang
Pin Wang is a scholar working on Molecular Biology, Oncology, Immunology, Genetics and Biomedical Engineering, having authored 145 papers that have together received 6.4k indexed citations. Recurring topics across this work include CAR-T cell therapy research (41 papers), Virus-based gene therapy research (37 papers), RNA Interference and Gene Delivery (33 papers), Immunotherapy and Immune Responses (21 papers), Immune Cell Function and Interaction (19 papers), Advanced biosensing and bioanalysis techniques (10 papers), Nanoparticle-Based Drug Delivery (9 papers) and T-cell and B-cell Immunology (8 papers). The work is most often cited by research in Immunology (1.8k citations), Oncology (2.0k citations), Cancer Research (836 citations), Biomaterials (800 citations) and Molecular Biology (2.9k citations). Pin Wang has collaborated with scholars based in United States, China and South Korea. Frequent co-authors include Kye‐Il Joo, Yarong Liu, Li Lin, Xuetao Cao, Biliang Hu, Jin Hou, Xingguang Liu, Feng Ma, Zhugang Wang and Elizabeth L. Siegler. Their work appears in journals such as Human Gene Therapy, Molecular Therapy, The Journal of Immunology, PLoS ONE and Nature Communications.
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.