Yu Ma
Impact in
- Modeling and Simulation top 1%
- COVID-19 epidemiological studies
- Rehabilitation top 2%
- Wound Healing and Treatments
Papers in
-
- RNA modifications and cancer 6
- Circular RNAs in diseases 5
- Epidemiology 17
- Co-authors
- Timothy C. Hall (4 shared papers)David G. Armstrong (16 shared papers)S. M. Sun (1 shared paper)Leslie M. Hoffman (2 shared papers)John W. Pyne (1 shared paper)Richard F. Barker (2 shared papers)F. A. Bliss (1 shared paper)David H. Gutmann (5 shared papers)
- Journals
- Frontiers in Pharmacology (5 papers)Journal of Clinical Oncology (4 papers)INTERNATIONAL JOURNAL OF SYSTEMATIC AND EVOLUTIONARY MICROBIOLOGY (3 papers)Scientific Reports (3 papers)Frontiers in Endocrinology (3 papers)
- Partner nations
- ChinaUnited StatesGermany
In The Last Decade
Yu Ma
167 papers receiving 3.2k citations
Peers
Comparison fields: 5 of 174
- Modeling and Simulation 243
- Rehabilitation 143
- Infectious Diseases 379
- Endocrinology, Diabetes and Metabolism 227
- Urology 78
Countries citing papers authored by Yu Ma
This map shows the geographic impact of Yu Ma'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 Yu Ma with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Yu Ma more than expected).
Fields of papers citing papers by Yu Ma
This network shows the impact of papers produced by Yu Ma. 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 Yu Ma. The network helps show where Yu Ma may publish in the future.
Co-authors
The 25 scholars most cited alongside Yu Ma, 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 180 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2020 | 310 | |
| 2 | 1978 | 186 | |
| 3 | 2018 | 108 | |
| 4 | 2020 | 94 | |
| 5 | 1982 | 89 | |
| 6 | 2023 | 68 | |
| 7 | 2021 | 66 | |
| 8 | 2009 | 64 | |
| 9 | 2009 | 61 | |
| 10 | 2018 | 61 | |
| 11 | 2017 | 60 | |
| 12 | 2018 | 57 | |
| 13 | 2000 | 57 | |
| 14 | 2019 | 53 | |
| 15 | 2020 | 52 | |
| 16 | 2020 | 52 | |
| 17 | 2008 | 51 | |
| 18 | 2016 | 50 | |
| 19 | 2007 | 49 | |
| 20 | 2019 | 48 |
About Yu Ma
Yu Ma is a scholar working on Molecular Biology, Epidemiology, Cancer Research, Endocrinology, Diabetes and Metabolism and Immunology, having authored 180 papers that have together received 3.3k indexed citations. Recurring topics across this work include Diabetic Foot Ulcer Assessment and Management (10 papers), Wound Healing and Treatments (8 papers), RNA modifications and cancer (6 papers), Cancer-related molecular mechanisms research (5 papers), Cancer, Hypoxia, and Metabolism (5 papers), COVID-19 epidemiological studies (5 papers), Immune cells in cancer (5 papers) and Circular RNAs in diseases (5 papers). The work is most often cited by research in Modeling and Simulation (243 citations), Rehabilitation (143 citations), Infectious Diseases (379 citations), Endocrinology, Diabetes and Metabolism (227 citations) and Urology (78 citations). Yu Ma has collaborated with scholars based in China, United States and Germany. Frequent co-authors include Timothy C. Hall, David G. Armstrong, S. M. Sun, Leslie M. Hoffman, John W. Pyne, Richard F. Barker, F. A. Bliss, David H. Gutmann, Siyuan Chen and Shunli Rui. Their work appears in journals such as Frontiers in Pharmacology, Journal of Clinical Oncology, INTERNATIONAL JOURNAL OF SYSTEMATIC AND EVOLUTIONARY MICROBIOLOGY, Scientific Reports and Frontiers in Endocrinology.
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.