Jin Ma
Impact in
- Aging top 5%
- Physiology top 10%
- Telomeres, Telomerase, and Senescence
Papers in
-
- RNA Interference and Gene Delivery 4
- Inflammasome and immune disorders 3
- RNA modifications and cancer 3
- DNA Repair Mechanisms 2
- Surgery 11
- Kawasaki Disease and Coronary Complications 10
- Co-authors
- Asha S. Multani (3 shared papers)Sandy Chang (3 shared papers)Sen Pathak (2 shared papers)Yibin Deng (2 shared papers)Susan M. Bailey (1 shared paper)Purnima R. Laud (1 shared paper)Ling Wu (1 shared paper)Michel Lebel (1 shared paper)
- Journals
- Pediatric Research (3 papers)International Immunopharmacology (2 papers)Medicinal Chemistry Research (1 paper)Horticultural Plant Journal (1 paper)Gene (1 paper)
- Partner nations
- ChinaUnited StatesCanada
In The Last Decade
Jin Ma
41 papers receiving 849 citations
Peers
Comparison fields: 5 of 78
- Aging 39
- Physiology 271
- Cancer Research 120
- Molecular Biology 516
- Plant Science 194
Countries citing papers authored by Jin Ma
This map shows the geographic impact of Jin 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 Jin Ma with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jin Ma more than expected).
Fields of papers citing papers by Jin Ma
This network shows the impact of papers produced by Jin 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 Jin Ma. The network helps show where Jin Ma may publish in the future.
Co-authors
The 25 scholars most cited alongside Jin 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 44 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2005 | 157 | |
| 2 | 2015 | 120 | |
| 3 | 2006 | 94 | |
| 4 | 2008 | 81 | |
| 5 | 2019 | 54 | |
| 6 | 2015 | 49 | |
| 7 | 2017 | 26 | |
| 8 | 2014 | 23 | |
| 9 | 2021 | 19 | |
| 10 | 2015 | 19 | |
| 11 | 2022 | 16 | |
| 12 | 2020 | 14 | |
| 13 | 2019 | 13 | |
| 14 | 2022 | 12 | |
| 15 | 2015 | 12 | |
| 16 | 2014 | 12 | |
| 17 | 2024 | 11 | |
| 18 | 2021 | 10 | |
| 19 | 2023 | 10 | |
| 20 | 2022 | 10 |
About Jin Ma
Jin Ma is a scholar working on Molecular Biology, Surgery, Pulmonary and Respiratory Medicine, Plant Science and Cancer Research, having authored 44 papers that have together received 860 indexed citations. Recurring topics across this work include Kawasaki Disease and Coronary Complications (10 papers), Coronary Artery Anomalies (5 papers), RNA Interference and Gene Delivery (4 papers), MicroRNA in disease regulation (4 papers), Telomeres, Telomerase, and Senescence (3 papers), Inflammasome and immune disorders (3 papers), RNA modifications and cancer (3 papers) and DNA Repair Mechanisms (2 papers). The work is most often cited by research in Aging (39 citations), Physiology (271 citations), Cancer Research (120 citations), Molecular Biology (516 citations) and Plant Science (194 citations). Jin Ma has collaborated with scholars based in China, United States and Canada. Frequent co-authors include Asha S. Multani, Sandy Chang, Sen Pathak, Yibin Deng, Susan M. Bailey, Purnima R. Laud, Ling Wu, Michel Lebel, Charles V. Kingsley and Ronald A. DePinho. Their work appears in journals such as Pediatric Research, International Immunopharmacology, Medicinal Chemistry Research, Horticultural Plant Journal and Gene.
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.