Maya Ramdas
Impact in
- Clinical Biochemistry top 1%
- Advanced Glycation End Products research
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- Natural Antidiabetic Agents Studies
- Diet, Metabolism, and Disease
- Diabetes, Cardiovascular Risks, and Lipoproteins
Papers in
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- Advanced Glycation End Products research 3
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- Hormonal Regulation and Hypertension 2
- Natural Antidiabetic Agents Studies 2
- Co-authors
- Helen Vlassara (3 shared papers)Weijing Cai (3 shared papers)Gary E. Striker (3 shared papers)Li Zhu (3 shared papers)Xue Chen (2 shared papers)Jaime Uribarri (2 shared papers)Susan A. Goodman (2 shared papers)Renata Pyzik (2 shared papers)
- Journals
- Hormone and Metabolic Research (2 papers)Canadian Journal of Physiology and Pharmacology (1 paper)Cardiorenal Medicine (1 paper)Journal of Trace Elements in Medicine and Biology (1 paper)Diabetes Care (1 paper)
- Partner nations
- United StatesIsraelIndia
In The Last Decade
Maya Ramdas
8 papers receiving 677 citations
Peers
Comparison fields: 5 of 70
- Clinical Biochemistry 422
- Endocrinology, Diabetes and Metabolism 246
- Geriatrics and Gerontology 24
- Physiology 140
- Nutrition and Dietetics 71
Countries citing papers authored by Maya Ramdas
This map shows the geographic impact of Maya Ramdas'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 Maya Ramdas with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Maya Ramdas more than expected).
Fields of papers citing papers by Maya Ramdas
This network shows the impact of papers produced by Maya Ramdas. 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 Maya Ramdas. The network helps show where Maya Ramdas may publish in the future.
Co-authors
The 19 scholars most cited alongside Maya Ramdas, 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 | 2011 | 290 | |
| 2 | 2012 | 279 | |
| 3 | 2013 | 63 | |
| 4 | 2014 | 19 | |
| 5 | 2012 | 13 | |
| 6 | 2014 | 13 | |
| 7 | 2018 | 11 | |
| 8 | 2016 | 2 |
About Maya Ramdas
Maya Ramdas is a scholar working on Clinical Biochemistry, Endocrinology, Diabetes and Metabolism, Physiology, Cardiology and Cardiovascular Medicine and Cancer Research, having authored 8 papers that have together received 690 indexed citations. Recurring topics across this work include Advanced Glycation End Products research (3 papers), Biochemical effects in animals (2 papers), Hormonal Regulation and Hypertension (2 papers), Metabolism, Diabetes, and Cancer (2 papers), Natural Antidiabetic Agents Studies (2 papers), Renin-Angiotensin System Studies (1 paper), Pancreatic function and diabetes (1 paper) and Lipoproteins and Cardiovascular Health (1 paper). The work is most often cited by research in Clinical Biochemistry (422 citations), Endocrinology, Diabetes and Metabolism (246 citations), Geriatrics and Gerontology (24 citations), Physiology (140 citations) and Nutrition and Dietetics (71 citations). Maya Ramdas has collaborated with scholars based in United States, Israel and India. Frequent co-authors include Helen Vlassara, Weijing Cai, Gary E. Striker, Li Zhu, Xue Chen, Jaime Uribarri, Susan A. Goodman, Renata Pyzik, Eddy Karnieli and Michal Armoni. Their work appears in journals such as Hormone and Metabolic Research, Canadian Journal of Physiology and Pharmacology, Cardiorenal Medicine, Journal of Trace Elements in Medicine and Biology and Diabetes Care.
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.