Lin Wang
Impact in
- Immunology top 1%
- Immunotherapy and Immune Responses
- Cancer Research top 1%
- MicroRNA in disease regulation
- Cancer-related molecular mechanisms research
Papers in
-
- Ubiquitin and proteasome pathways 19
- Wnt/β-catenin signaling in development and cancer 11
- Oncology 58
- Cytokine Signaling Pathways and Interactions 20
- Cancer-related Molecular Pathways 10
- Co-authors
- Hua Yu (4 shared papers)Drew M. Pardoll (3 shared papers)Tangsheng Yi (3 shared papers)Marcin Kortylewski (3 shared papers)Jihong Pan (30 shared papers)Defu Zeng (2 shared papers)Feng Xu (6 shared papers)Bo Han (17 shared papers)
- Journals
- Blood (8 papers)Oncotarget (6 papers)Arthritis Research & Therapy (6 papers)Cancer Research (6 papers)Scientific Reports (5 papers)
- Partner nations
- ChinaUnited StatesCanada
In The Last Decade
Lin Wang
314 papers receiving 8.5k citations
Lin Wang's Hit Papers
Peers
Comparison fields: 5 of 168
- Immunology 1.5k
- Cancer Research 963
- Parasitology 428
- Oncology 1.4k
- Molecular Biology 2.9k
Countries citing papers authored by Lin Wang
This map shows the geographic impact of Lin 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 Lin Wang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Lin Wang more than expected).
Fields of papers citing papers by Lin Wang
This network shows the impact of papers produced by Lin 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 Lin Wang. The network helps show where Lin Wang may publish in the future.
Co-authors
The 25 scholars most cited alongside Lin 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 322 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | IL-17 can promote tumor growth through an IL-6–Stat3 signaling pathway Hit paper breakdown → | 2009 | 681 |
| 2 | 2011 | 316 | |
| 3 | 2005 | 282 | |
| 4 | 2013 | 224 | |
| 5 | 2012 | 185 | |
| 6 | 2011 | 169 | |
| 7 | 2012 | 155 | |
| 8 | 2010 | 149 | |
| 9 | 2012 | 129 | |
| 10 | 2005 | 124 | |
| 11 | 2002 | 115 | |
| 12 | 2020 | 110 | |
| 13 | 2019 | 109 | |
| 14 | 2009 | 102 | |
| 15 | 2013 | 98 | |
| 16 | 2015 | 83 | |
| 17 | 2017 | 81 | |
| 18 | 2020 | 81 | |
| 19 | 2021 | 77 | |
| 20 | 2008 | 76 |
About Lin Wang
Lin Wang is a scholar working on Molecular Biology, Oncology, Immunology, Cell Biology and Cancer Research, having authored 322 papers that have together received 8.6k indexed citations. Recurring topics across this work include Cytokine Signaling Pathways and Interactions (20 papers), Ubiquitin and proteasome pathways (19 papers), Wnt/β-catenin signaling in development and cancer (11 papers), Prostate Cancer Treatment and Research (10 papers), Cancer-related molecular mechanisms research (10 papers), Cancer-related Molecular Pathways (10 papers), Endoplasmic Reticulum Stress and Disease (10 papers) and Toxoplasma gondii Research Studies (10 papers). The work is most often cited by research in Immunology (1.5k citations), Cancer Research (963 citations), Parasitology (428 citations), Oncology (1.4k citations) and Molecular Biology (2.9k citations). Lin Wang has collaborated with scholars based in China, United States and Canada. Frequent co-authors include Hua Yu, Drew M. Pardoll, Tangsheng Yi, Marcin Kortylewski, Jihong Pan, Defu Zeng, Feng Xu, Bo Han, Guoyou Huang and Tian Jian Lu. Their work appears in journals such as Blood, Oncotarget, Arthritis Research & Therapy, Cancer Research and Scientific Reports.
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.