Ferenc Torma
Impact in
- Electrochemistry top 5%
- Electrochemical Analysis and Applications
- Bioengineering top 5%
- Analytical Chemistry and Sensors
Papers in
- Physiology 14
- Adipose Tissue and Metabolism 9
- Diet and metabolism studies 2
-
- Epigenetics and DNA Methylation 4
- Gut microbiota and health 2
- Co-authors
- Zsolt Radák (20 shared papers)Klára Tóth (2 shared papers)Mihály Kádár (1 shared paper)Enikő Tatár (1 shared paper)Tatsuya Mimura (3 shared papers)Mátyás Jókai (8 shared papers)Zoltán Gombos (6 shared papers)Erika Koltai (10 shared papers)
- Journals
- Journal of sport and health science (2 papers)Free Radical Biology and Medicine (2 papers)Biogerontology (2 papers)Aging Cell (2 papers)Sports Medicine and Health Science (2 papers)
- Partner nations
- HungaryJapanUnited States
In The Last Decade
Ferenc Torma
26 papers receiving 523 citations
Peers
Comparison fields: 5 of 93
- Electrochemistry 96
- Bioengineering 75
- Aging 14
- Rehabilitation 47
- Complementary and alternative medicine 52
Countries citing papers authored by Ferenc Torma
This map shows the geographic impact of Ferenc Torma'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 Ferenc Torma with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ferenc Torma more than expected).
Fields of papers citing papers by Ferenc Torma
This network shows the impact of papers produced by Ferenc Torma. 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 Ferenc Torma. The network helps show where Ferenc Torma may publish in the future.
Co-authors
The 25 scholars most cited alongside Ferenc Torma, 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 27 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2018 | 85 | |
| 2 | 2008 | 83 | |
| 3 | 2023 | 61 | |
| 4 | 2019 | 58 | |
| 5 | 2009 | 27 | |
| 6 | 2019 | 25 | |
| 7 | 2020 | 24 | |
| 8 | 2014 | 23 | |
| 9 | 2023 | 15 | |
| 10 | 2024 | 14 | |
| 11 | 2018 | 13 | |
| 12 | 2023 | 13 | |
| 13 | 2023 | 12 | |
| 14 | 2021 | 12 | |
| 15 | 2007 | 10 | |
| 16 | 2014 | 10 | |
| 17 | 2021 | 9 | |
| 18 | 2009 | 7 | |
| 19 | 2021 | 6 | |
| 20 | 2025 | 6 |
About Ferenc Torma
Ferenc Torma is a scholar working on Physiology, Molecular Biology, Rehabilitation, Geriatrics and Gerontology and Cognitive Neuroscience, having authored 27 papers that have together received 529 indexed citations. Recurring topics across this work include Adipose Tissue and Metabolism (9 papers), Epigenetics and DNA Methylation (4 papers), Sirtuins and Resveratrol in Medicine (3 papers), Cardiovascular and exercise physiology (3 papers), Exercise and Physiological Responses (3 papers), Diet and metabolism studies (2 papers), Multisensory perception and integration (2 papers) and Gut microbiota and health (2 papers). The work is most often cited by research in Electrochemistry (96 citations), Bioengineering (75 citations), Aging (14 citations), Rehabilitation (47 citations) and Complementary and alternative medicine (52 citations). Ferenc Torma has collaborated with scholars based in Hungary, Japan and United States. Frequent co-authors include Zsolt Radák, Klára Tóth, Mihály Kádár, Enikő Tatár, Tatsuya Mimura, Mátyás Jókai, Zoltán Gombos, Erika Koltai, Masaki Takeda and István Boldogh. Their work appears in journals such as Journal of sport and health science, Free Radical Biology and Medicine, Biogerontology, Aging Cell and Sports Medicine and Health Science.
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.