Majid Vakilynejad
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- Diabetes Treatment and Management 8
- Diabetes Management and Research 5
- Hormonal Regulation and Hypertension 4
- Pharmacology top 10%
- Pharmacogenetics and Drug Metabolism 2
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- Multiple Myeloma Research and Treatments 2
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- Statistical Methods in Clinical Trials 2
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- Pharmaceutical studies and practices 2
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- Cancer Treatment and Pharmacology 2
- Co-authors
- Eckhard LeifkePrabhakar ViswanathanJohn MarcinakBenhuai XieCharlie CaoCharles BurantHimanshu NaikGëzim Lahu
- Journals
- Clinical and Translational Science (6 papers)Clinical Pharmacology & Therapeutics (4 papers)CPT Pharmacometrics & Systems Pharmacology (3 papers)
- Partner nations
- United StatesJapanSwitzerland
In The Last Decade
Majid Vakilynejad
27 papers receiving 568 citations
Peers
Comparison fields: 5 of 81
- Endocrinology, Diabetes and Metabolism 298
- Pharmacology 76
- Health Information Management 30
- Surgery 218
- Molecular Biology 270
Countries citing papers authored by Majid Vakilynejad
This map shows the geographic impact of Majid Vakilynejad'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 Majid Vakilynejad with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Majid Vakilynejad more than expected).
Fields of papers citing papers by Majid Vakilynejad
This network shows the impact of papers produced by Majid Vakilynejad. 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 Majid Vakilynejad. The network helps show where Majid Vakilynejad may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Majid Vakilynejad, 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 | 2025 | 1 | |
| 2 | 2025 | 2 | |
| 3 | 2024 | 0 | |
| 4 | 2024 | 3 | |
| 5 | 2023 | 8 | |
| 6 | 2023 | 5 | |
| 7 | 2023 | 3 | |
| 8 | 2019 | 5 | |
| 9 | 2018 | 1 | |
| 10 | 2018 | 6 | |
| 11 | 2018 | 2 | |
| 12 | 2017 | 43 | |
| 13 | 2015 | 8 | |
| 14 | 2015 | 2 | |
| 15 | 2013 | 3 | |
| 16 | 2013 | 13 | |
| 17 | 2012 | 75 | |
| 18 | 2012 | 212 | |
| 19 | 2011 | 74 | |
| 20 | 1993 | 38 |
About Majid Vakilynejad
Majid Vakilynejad is a scholar working on Endocrinology, Diabetes and Metabolism, Transplantation, Pharmacology, Nephrology and Hematology, having authored 28 papers that have together received 586 indexed citations. Recurring topics across this work include Diabetes Treatment and Management (8 papers), Diabetes Management and Research (5 papers), Hormonal Regulation and Hypertension (4 papers), Multiple Myeloma Research and Treatments (2 papers), Pharmacogenetics and Drug Metabolism (2 papers), Statistical Methods in Clinical Trials (2 papers), Pharmaceutical studies and practices (2 papers) and Cancer Treatment and Pharmacology (2 papers). The work is most often cited by research in Endocrinology, Diabetes and Metabolism (298 citations), Pharmacology (76 citations), Health Information Management (30 citations), Surgery (218 citations) and Molecular Biology (270 citations). Majid Vakilynejad has collaborated with scholars based in United States, Japan and Switzerland. Frequent co-authors include Eckhard Leifke, Prabhakar Viswanathan, John Marcinak, Benhuai Xie, Charlie Cao, Charles Burant, Himanshu Naik, Gëzim Lahu, Jingtao Wu and Tomoaki Higuchi. Their work appears in journals such as Clinical and Translational Science, Clinical Pharmacology & Therapeutics, CPT Pharmacometrics & Systems Pharmacology, The Journal of Clinical Pharmacology and Journal of Pharmacokinetics and Pharmacodynamics.
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.