Qing Ye
Impact in
- Oncology top 2%
- Cancer-related Molecular Pathways
- Molecular Biology top 2%
- Melanoma and MAPK Pathways
- PI3K/AKT/mTOR signaling in cancer
- RNA modifications and cancer
Papers in
-
- RNA modifications and cancer 10
- PI3K/AKT/mTOR signaling in cancer 8
- Circular RNAs in diseases 5
-
- MicroRNA in disease regulation 7
- Cancer-related molecular mechanisms research 6
- Cancer Genomics and Diagnostics 4
- Co-authors
- David B. Solit (5 shared papers)Neal Rosen (6 shared papers)Christine A. Pratilas (2 shared papers)Jose Lobo (2 shared papers)Qing‐Bai She (10 shared papers)William R. Sellers (2 shared papers)Ayana Sawai (2 shared papers)Todd R. Golub (1 shared paper)
- Journals
- International Journal of Molecular Sciences (6 papers)Scientific Reports (4 papers)Cancer Research (4 papers)Cancers (3 papers)Nature Communications (2 papers)
- Partner nations
- United StatesChinaGermany
In The Last Decade
Qing Ye
70 papers receiving 3.5k citations
Qing Ye's Hit Papers
Peers
Comparison fields: 5 of 142
- Oncology 1.1k
- Molecular Biology 2.6k
- Cancer Research 479
- Pathology and Forensic Medicine 398
- Computational Theory and Mathematics 286
Countries citing papers authored by Qing Ye
This map shows the geographic impact of Qing Ye'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 Qing Ye with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Qing Ye more than expected).
Fields of papers citing papers by Qing Ye
This network shows the impact of papers produced by Qing Ye. 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 Qing Ye. The network helps show where Qing Ye may publish in the future.
Co-authors
The 25 scholars most cited alongside Qing Ye, 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 75 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | BRAF mutation predicts sensitivity to MEK inhibition Hit paper breakdown → | 2005 | 1013 |
| 2 | 2009 | 455 | |
| 3 | 2005 | 352 | |
| 4 | 1998 | 217 | |
| 5 | 2008 | 144 | |
| 6 | 2010 | 133 | |
| 7 | 1999 | 101 | |
| 8 | 2021 | 93 | |
| 9 | 2017 | 84 | |
| 10 | 2017 | 71 | |
| 11 | 2020 | 71 | |
| 12 | 2015 | 52 | |
| 13 | 2017 | 48 | |
| 14 | 2014 | 44 | |
| 15 | 2000 | 34 | |
| 16 | 2019 | 31 | |
| 17 | 2012 | 30 | |
| 18 | 2017 | 29 | |
| 19 | 2017 | 28 | |
| 20 | 2014 | 25 |
About Qing Ye
Qing Ye is a scholar working on Molecular Biology, Cancer Research, Oncology, Pulmonary and Respiratory Medicine and Biomaterials, having authored 75 papers that have together received 3.5k indexed citations. Recurring topics across this work include RNA modifications and cancer (10 papers), PI3K/AKT/mTOR signaling in cancer (8 papers), MicroRNA in disease regulation (7 papers), Cancer-related molecular mechanisms research (6 papers), Circular RNAs in diseases (5 papers), Parasites and Host Interactions (4 papers), Ferroptosis and cancer prognosis (4 papers) and Cancer Genomics and Diagnostics (4 papers). The work is most often cited by research in Oncology (1.1k citations), Molecular Biology (2.6k citations), Cancer Research (479 citations), Pathology and Forensic Medicine (398 citations) and Computational Theory and Mathematics (286 citations). Qing Ye has collaborated with scholars based in United States, China and Germany. Frequent co-authors include David B. Solit, Neal Rosen, Christine A. Pratilas, Jose Lobo, Qing‐Bai She, William R. Sellers, Ayana Sawai, Todd R. Golub, Judith S. Sebolt–Leopold and Iman Osman. Their work appears in journals such as International Journal of Molecular Sciences, Scientific Reports, Cancer Research, Cancers 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.