Wei Tang
Impact in
- Cancer Research top 2%
- Cancer-related molecular mechanisms research
- Cancer Genomics and Diagnostics
- Hepatology top 2%
- Hepatitis C virus research
Papers in
-
- Epigenetics and DNA Methylation 7
- Metabolism, Diabetes, and Cancer 5
- Oncology 18
- Polyomavirus and related diseases 4
- Co-authors
- Colin Sumners (6 shared papers)Mohan K. Raizada (5 shared papers)Stefan Ambs (30 shared papers)Blanka Železná (3 shared papers)William R. Folk (4 shared papers)Tiffany H. Dorsey (19 shared papers)Ludmila Prokunina‐Olsson (14 shared papers)Jacques Piette (1 shared paper)
- Journals
- Cancer Research (4 papers)Molecular and Cellular Biology (3 papers)Genome biology (3 papers)Cancer Epidemiology Biomarkers & Prevention (3 papers)Hepatology (2 papers)
- Partner nations
- United StatesChinaGermany
In The Last Decade
Wei Tang
84 papers receiving 2.9k citations
Wei Tang's Hit Papers
Peers
Comparison fields: 5 of 112
- Cancer Research 596
- Hepatology 265
- Oncology 606
- Molecular Biology 1.4k
- Immunology 317
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 89 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | Single‐cell analysis reveals cancer stem cell heterogeneity in hepatocellular carcinoma Hit paper breakdown → | 2018 | 274 |
| 2 | 2016 | 234 | |
| 3 | 1991 | 232 | |
| 4 | 1988 | 178 | |
| 5 | 2018 | 121 | |
| 6 | 2016 | 95 | |
| 7 | 2018 | 93 | |
| 8 | 2019 | 86 | |
| 9 | 2013 | 76 | |
| 10 | 2013 | 73 | |
| 11 | 2014 | 71 | |
| 12 | 2017 | 66 | |
| 13 | 1987 | 48 | |
| 14 | 2019 | 48 | |
| 15 | 2021 | 47 | |
| 16 | 2019 | 45 | |
| 17 | 2016 | 45 | |
| 18 | 2021 | 44 | |
| 19 | 2017 | 42 | |
| 20 | 1994 | 41 |
About Wei Tang
Wei Tang is a scholar working on Molecular Biology, Oncology, Cancer Research, Immunology and Pulmonary and Respiratory Medicine, having authored 89 papers that have together received 2.9k indexed citations. Recurring topics across this work include Prostate Cancer Treatment and Research (9 papers), Epigenetics and DNA Methylation (7 papers), Cancer-related molecular mechanisms research (7 papers), Cancer, Hypoxia, and Metabolism (6 papers), Metabolism, Diabetes, and Cancer (5 papers), interferon and immune responses (5 papers), Polyomavirus and related diseases (4 papers) and Hepatitis C virus research (4 papers). The work is most often cited by research in Cancer Research (596 citations), Hepatology (265 citations), Oncology (606 citations), Molecular Biology (1.4k citations) and Immunology (317 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, Jacques Piette, Moshé Yaniv and M. Elena Martı́n. Their work appears in journals such as Cancer Research, Molecular and Cellular Biology, Genome biology, Cancer Epidemiology Biomarkers & Prevention and Hepatology.
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.