Jianing Ma
Impact in
-
- Tuberculosis Research and Epidemiology
- COVID-19 Clinical Research Studies
Papers in
- Surgery 7
- Infectious Diseases and Tuberculosis 2
-
- Congenital Heart Disease Studies 2
- Co-authors
- Peng Zheng (3 shared papers)Theo Vos (2 shared papers)Hmwe Hmwe Kyu (4 shared papers)Jorge R Ledesma (3 shared papers)Jennifer M. Ross (1 shared paper)Christopher J L Murray (3 shared papers)Matthew Arentz (1 shared paper)Craig H. Selzman (1 shared paper)
- Journals
- BMC Infectious Diseases (3 papers)Digestive Diseases and Sciences (2 papers)Muscle & Nerve (1 paper)Bioresource Technology (1 paper)Synthetic and Systems Biotechnology (1 paper)
- Partner nations
- United StatesChinaSingapore
In The Last Decade
Jianing Ma
15 papers receiving 134 citations
Peers
Comparison fields: 5 of 57
- Infectious Diseases 48
- Modeling and Simulation 7
- Biotechnology 11
- Epidemiology 38
- Nephrology 7
Countries citing papers authored by Jianing Ma
This map shows the geographic impact of Jianing 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 Jianing Ma with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jianing Ma more than expected).
Fields of papers citing papers by Jianing Ma
This network shows the impact of papers produced by Jianing 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 Jianing Ma. The network helps show where Jianing Ma may publish in the future.
Co-authors
The 25 scholars most cited alongside Jianing 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
| # | Work | ||
|---|---|---|---|
| 1 | 2021 | 28 | |
| 2 | 2018 | 20 | |
| 3 | 2023 | 17 | |
| 4 | 2022 | 17 | |
| 5 | 2019 | 16 | |
| 6 | 2024 | 8 | |
| 7 | 2024 | 7 | |
| 8 | 2023 | 5 | |
| 9 | 2022 | 5 | |
| 10 | 2023 | 4 | |
| 11 | 2023 | 3 | |
| 12 | 2025 | 2 | |
| 13 | 2019 | 1 | |
| 14 | 2024 | 1 | |
| 15 | 2020 | 1 | |
| 16 | 2025 | 0 | |
| 17 | 2025 | 0 |
About Jianing Ma
Jianing Ma is a scholar working on Surgery, Epidemiology, Infectious Diseases, Cardiology and Cardiovascular Medicine and Pulmonary and Respiratory Medicine, having authored 17 papers that have together received 135 indexed citations. Recurring topics across this work include Tuberculosis Research and Epidemiology (4 papers), COVID-19 Clinical Research Studies (2 papers), Infectious Diseases and Tuberculosis (2 papers), Congenital Heart Disease Studies (2 papers), Renal and Vascular Pathologies (1 paper), Metabolism, Diabetes, and Cancer (1 paper), Neuroscience and Neural Engineering (1 paper) and COVID-19 diagnosis using AI (1 paper). The work is most often cited by research in Infectious Diseases (48 citations), Modeling and Simulation (7 citations), Biotechnology (11 citations), Epidemiology (38 citations) and Nephrology (7 citations). Jianing Ma has collaborated with scholars based in United States, China and Singapore. Frequent co-authors include Peng Zheng, Theo Vos, Hmwe Hmwe Kyu, Jorge R Ledesma, Jennifer M. Ross, Christopher J L Murray, Matthew Arentz, Craig H. Selzman, Alfred K. Cheung and Jingwen Zhou. Their work appears in journals such as BMC Infectious Diseases, Digestive Diseases and Sciences, Muscle & Nerve, Bioresource Technology and Synthetic and Systems Biotechnology.
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.