Daming Gao
Impact in
- Geriatrics and Gerontology top 2%
- Oncology top 2%
- Cancer-related Molecular Pathways
Papers in
-
- Ubiquitin and proteasome pathways 29
- PI3K/AKT/mTOR signaling in cancer 10
- Oncology 25
- Cancer-related Molecular Pathways 15
- Co-authors
- Wenyi Wei (28 shared papers)Hiroyuki Inuzuka (24 shared papers)Lixin Wan (18 shared papers)Shavali Shaik (10 shared papers)Alan Tseng (7 shared papers)Hidefumi Fukushima (11 shared papers)Alan W. Lau (8 shared papers)Pengda Liu (9 shared papers)
- Journals
- Molecular Cell (4 papers)Hepatology (4 papers)Cell Research (3 papers)Fusion Engineering and Design (3 papers)Cancer Research (3 papers)
- Partner nations
- ChinaUnited StatesJapan
In The Last Decade
Daming Gao
75 papers receiving 3.9k citations
Daming Gao's Hit Papers
Peers
Comparison fields: 5 of 121
- Geriatrics and Gerontology 143
- Oncology 1.1k
- Molecular Biology 2.9k
- Cancer Research 566
- Cell Biology 533
Countries citing papers authored by Daming Gao
This map shows the geographic impact of Daming Gao'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 Daming Gao with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Daming Gao more than expected).
Fields of papers citing papers by Daming Gao
This network shows the impact of papers produced by Daming Gao. 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 Daming Gao. The network helps show where Daming Gao may publish in the future.
Co-authors
The 25 scholars most cited alongside Daming Gao, 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 77 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | SCFFBW7 regulates cellular apoptosis by targeting MCL1 for ubiquitylation and destruction Hit paper breakdown → | 2011 | 541 |
| 2 | 2016 | 219 | |
| 3 | 2009 | 213 | |
| 4 | 2011 | 210 | |
| 5 | 2012 | 176 | |
| 6 | 2010 | 170 | |
| 7 | 2015 | 154 | |
| 8 | 2015 | 123 | |
| 9 | 2017 | 106 | |
| 10 | 2010 | 102 | |
| 11 | 2011 | 97 | |
| 12 | 2011 | 87 | |
| 13 | 2004 | 79 | |
| 14 | 2012 | 75 | |
| 15 | 2010 | 75 | |
| 16 | 2012 | 74 | |
| 17 | SIRT1 phosphorylation by AMP-activated protein kinase regulates p53 acetylation. | 2014 | 73 |
| 18 | 2012 | 72 | |
| 19 | 2017 | 70 | |
| 20 | 2022 | 67 |
About Daming Gao
Daming Gao is a scholar working on Molecular Biology, Oncology, Cell Biology, Cancer Research and Biomedical Engineering, having authored 77 papers that have together received 3.9k indexed citations. Recurring topics across this work include Ubiquitin and proteasome pathways (29 papers), Cancer-related Molecular Pathways (15 papers), PI3K/AKT/mTOR signaling in cancer (10 papers), Superconducting Materials and Applications (8 papers), Microtubule and mitosis dynamics (8 papers), Magnetic confinement fusion research (8 papers), Cancer, Hypoxia, and Metabolism (8 papers) and Particle accelerators and beam dynamics (6 papers). The work is most often cited by research in Geriatrics and Gerontology (143 citations), Oncology (1.1k citations), Molecular Biology (2.9k citations), Cancer Research (566 citations) and Cell Biology (533 citations). Daming Gao has collaborated with scholars based in China, United States and Japan. Frequent co-authors include Wenyi Wei, Hiroyuki Inuzuka, Lixin Wan, Shavali Shaik, Alan Tseng, Hidefumi Fukushima, Alan W. Lau, Pengda Liu, Steven P. Gygi and Alex Toker. Their work appears in journals such as Molecular Cell, Hepatology, Cell Research, Fusion Engineering and Design and 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.