Hailing Yang
Impact in
- Cell Biology top 2%
- Microtubule and mitosis dynamics
- Cellular Mechanics and Interactions
- Cancer Research top 10%
- MicroRNA in disease regulation
Papers in
-
- Ubiquitin and proteasome pathways 5
- Epigenetics and DNA Methylation 4
- Cell Biology 18
- Microtubule and mitosis dynamics 16
- Cellular Mechanics and Interactions 4
- Co-authors
- Fernando Cabral (14 shared papers)Anutosh Ganguly (10 shared papers)Robert C. Bast (19 shared papers)Zhen Lü (18 shared papers)Kamala D. Patel (3 shared papers)Malathi Hari (1 shared paper)Changqing Zeng (1 shared paper)Weiqun Mao (15 shared papers)
- Journals
- Journal of Biological Chemistry (4 papers)Molecular Cancer Therapeutics (3 papers)Autophagy (3 papers)International Immunopharmacology (2 papers)Oncotarget (2 papers)
- Partner nations
- United StatesChinaCanada
In The Last Decade
Hailing Yang
55 papers receiving 1.6k citations
Peers
Comparison fields: 5 of 109
- Cell Biology 459
- Cancer Research 236
- Oncology 352
- Molecular Biology 853
- Geriatrics and Gerontology 24
Countries citing papers authored by Hailing Yang
This map shows the geographic impact of Hailing Yang'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 Hailing Yang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Hailing Yang more than expected).
Fields of papers citing papers by Hailing Yang
This network shows the impact of papers produced by Hailing Yang. 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 Hailing Yang. The network helps show where Hailing Yang may publish in the future.
Co-authors
The 25 scholars most cited alongside Hailing Yang, 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 59 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2010 | 144 | |
| 2 | 2003 | 138 | |
| 3 | 2012 | 111 | |
| 4 | 2010 | 107 | |
| 5 | 2014 | 67 | |
| 6 | 2014 | 61 | |
| 7 | 2011 | 55 | |
| 8 | 2015 | 51 | |
| 9 | 2016 | 49 | |
| 10 | 2018 | 49 | |
| 11 | 2019 | 44 | |
| 12 | 2016 | 41 | |
| 13 | 2011 | 38 | |
| 14 | 2018 | 33 | |
| 15 | 2011 | 33 | |
| 16 | 2007 | 32 | |
| 17 | 2015 | 31 | |
| 18 | 2013 | 29 | |
| 19 | 2021 | 28 | |
| 20 | 2019 | 27 |
About Hailing Yang
Hailing Yang is a scholar working on Molecular Biology, Cell Biology, Epidemiology, Oncology and Cancer Research, having authored 59 papers that have together received 1.6k indexed citations. Recurring topics across this work include Microtubule and mitosis dynamics (16 papers), Autophagy in Disease and Therapy (9 papers), Ubiquitin and proteasome pathways (5 papers), Cancer Treatment and Pharmacology (5 papers), Cancer-related Molecular Pathways (5 papers), Ovarian cancer diagnosis and treatment (4 papers), Epigenetics and DNA Methylation (4 papers) and Cellular Mechanics and Interactions (4 papers). The work is most often cited by research in Cell Biology (459 citations), Cancer Research (236 citations), Oncology (352 citations), Molecular Biology (853 citations) and Geriatrics and Gerontology (24 citations). Hailing Yang has collaborated with scholars based in United States, China and Canada. Frequent co-authors include Fernando Cabral, Anutosh Ganguly, Robert C. Bast, Zhen Lü, Kamala D. Patel, Malathi Hari, Changqing Zeng, Weiqun Mao, Margie N. Sutton and Ritu Sharma. Their work appears in journals such as Journal of Biological Chemistry, Molecular Cancer Therapeutics, Autophagy, International Immunopharmacology and Oncotarget.
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.