Wei Tang
Impact in
- Cancer Research top 2%
- Cancer-related molecular mechanisms research
- Hepatology top 5%
- Hepatitis C virus research
Papers in
-
- Epigenetics and DNA Methylation 13
- Metabolism, Diabetes, and Cancer 5
- RNA Research and Splicing 4
- RNA modifications and cancer 4
- Oncology 23
- Co-authors
- Colin Sumners (6 shared papers)Mohan K. Raizada (5 shared papers)Stefan Ambs (29 shared papers)Blanka Železná (3 shared papers)William R. Folk (3 shared papers)Tiffany H. Dorsey (18 shared papers)Ludmila Prokunina‐Olsson (14 shared papers)Moshé Yaniv (1 shared paper)
- Journals
- Cancer Epidemiology Biomarkers & Prevention (3 papers)Cancer Research (3 papers)Genome biology (3 papers)Molecular and Cellular Biology (3 papers)Clinical Cancer Research (2 papers)
- Partner nations
- United StatesChinaGermany
In The Last Decade
Wei Tang
84 papers receiving 2.7k citations
Peers
Comparison fields: 5 of 115
- Cancer Research 687
- Hepatology 272
- Oncology 691
- Molecular Biology 1.5k
- Immunology 340
Countries citing papers authored by Wei Tang
This map shows the geographic impact of Wei Tang'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 Wei Tang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Wei Tang more than expected).
Fields of papers citing papers by Wei Tang
This network shows the impact of papers produced by Wei Tang. 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 Wei Tang. The network helps show where Wei Tang may publish in the future.
Co-authors
The 25 scholars most cited alongside Wei Tang, 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 88 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2018 | 267 | |
| 2 | 2016 | 225 | |
| 3 | 1991 | 216 | |
| 4 | 1988 | 178 | |
| 5 | 2018 | 118 | |
| 6 | 2016 | 91 | |
| 7 | 2018 | 89 | |
| 8 | 2013 | 76 | |
| 9 | 2019 | 73 | |
| 10 | 2013 | 72 | |
| 11 | 2014 | 69 | |
| 12 | 2017 | 65 | |
| 13 | 1987 | 48 | |
| 14 | 2021 | 45 | |
| 15 | 2019 | 45 | |
| 16 | 2019 | 44 | |
| 17 | 2017 | 41 | |
| 18 | 2016 | 41 | |
| 19 | 1992 | 40 | |
| 20 | 2021 | 40 |
About Wei Tang
Wei Tang is a scholar working on Molecular Biology, Oncology, Cancer Research, Pulmonary and Respiratory Medicine and Immunology, having authored 88 papers that have together received 2.8k indexed citations. Recurring topics across this work include Epigenetics and DNA Methylation (13 papers), Prostate Cancer Treatment and Research (12 papers), Cancer-related molecular mechanisms research (9 papers), Cancer, Hypoxia, and Metabolism (7 papers), Metabolism, Diabetes, and Cancer (5 papers), interferon and immune responses (5 papers), RNA Research and Splicing (4 papers) and RNA modifications and cancer (4 papers). The work is most often cited by research in Cancer Research (687 citations), Hepatology (272 citations), Oncology (691 citations), Molecular Biology (1.5k citations) and Immunology (340 citations). Wei Tang has collaborated with scholars based in United States, China and Germany. Frequent co-authors include Colin Sumners, Mohan K. Raizada, Stefan Ambs, Blanka Železná, William R. Folk, Tiffany H. Dorsey, Ludmila Prokunina‐Olsson, Moshé Yaniv, M. Elena Martı́n and Jacques Piette. Their work appears in journals such as Cancer Epidemiology Biomarkers & Prevention, Cancer Research, Genome biology, Molecular and Cellular Biology and Clinical Cancer Research.
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.