Yu Ma
Impact in
- Modeling and Simulation top 1%
- COVID-19 epidemiological studies
- Infectious Diseases top 2%
- SARS-CoV-2 and COVID-19 Research
- COVID-19 Clinical Research Studies
Papers in
-
- RNA modifications and cancer 7
- Epidemiology 26
- Co-authors
- Timothy C. Hall (3 shared papers)David G. Armstrong (16 shared papers)S. M. Sun (1 shared paper)John W. Pyne (1 shared paper)David H. Gutmann (5 shared papers)F. A. Bliss (1 shared paper)Richard F. Barker (1 shared paper)Leslie M. Hoffman (1 shared paper)
- Journals
- Frontiers in Pharmacology (5 papers)Journal of Clinical Oncology (4 papers)BMC Infectious Diseases (3 papers)Scientific Reports (3 papers)INTERNATIONAL JOURNAL OF SYSTEMATIC AND EVOLUTIONARY MICROBIOLOGY (3 papers)
- Partner nations
- ChinaUnited StatesSingapore
In The Last Decade
Yu Ma
161 papers receiving 3.0k citations
Peers
Comparison fields: 5 of 176
- Modeling and Simulation 332
- Infectious Diseases 557
- Rehabilitation 193
- Occupational Therapy 71
- Endocrinology, Diabetes and Metabolism 248
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 171 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2020 | 301 | |
| 2 | 1978 | 172 | |
| 3 | 2018 | 101 | |
| 4 | 2020 | 94 | |
| 5 | 1982 | 84 | |
| 6 | 2023 | 64 | |
| 7 | 2021 | 63 | |
| 8 | 2018 | 59 | |
| 9 | 2017 | 58 | |
| 10 | 2009 | 58 | |
| 11 | 2009 | 55 | |
| 12 | 2018 | 54 | |
| 13 | 2000 | 53 | |
| 14 | 2020 | 52 | |
| 15 | 2019 | 51 | |
| 16 | 2020 | 51 | |
| 17 | 2016 | 49 | |
| 18 | 2008 | 48 | |
| 19 | 2007 | 46 | |
| 20 | 2024 | 42 |
About Yu Ma
Yu Ma is a scholar working on Molecular Biology, Epidemiology, Infectious Diseases, Endocrinology, Diabetes and Metabolism and Cancer Research, having authored 171 papers that have together received 3.1k indexed citations. Recurring topics across this work include Diabetic Foot Ulcer Assessment and Management (13 papers), Wound Healing and Treatments (13 papers), SARS-CoV-2 and COVID-19 Research (10 papers), COVID-19 epidemiological studies (10 papers), RNA modifications and cancer (7 papers), Immune cells in cancer (6 papers), Cancer-related molecular mechanisms research (6 papers) and SARS-CoV-2 detection and testing (6 papers). The work is most often cited by research in Modeling and Simulation (332 citations), Infectious Diseases (557 citations), Rehabilitation (193 citations), Occupational Therapy (71 citations) and Endocrinology, Diabetes and Metabolism (248 citations). Yu Ma has collaborated with scholars based in China, United States and Singapore. Frequent co-authors include Timothy C. Hall, David G. Armstrong, S. M. Sun, John W. Pyne, David H. Gutmann, F. A. Bliss, Richard F. Barker, Leslie M. Hoffman, Siyuan Chen and Lei Luo. Their work appears in journals such as Frontiers in Pharmacology, Journal of Clinical Oncology, BMC Infectious Diseases, Scientific Reports and INTERNATIONAL JOURNAL OF SYSTEMATIC AND EVOLUTIONARY MICROBIOLOGY.
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.