Surendra Dasari
- Cancer Research top 1%
- Nephrology top 1%
- Renal Diseases and Glomerulopathies 16
- Molecular Biology top 1%
- Amyloidosis: Diagnosis, Treatment, Outcomes 70
- Physiology top 1%
- Adipose Tissue and Metabolism 25
- Hematology top 1%
- Multiple Myeloma Research and Treatments 22
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- Advanced Proteomics Techniques and Applications 18
- Mass Spectrometry Techniques and Applications 14
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- Muscle metabolism and nutrition 16
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- Monoclonal and Polyclonal Antibodies Research 14
- Co-authors
- Jean‐Pierre KocherLiguo WangHyun Jung ParkWei LiShengqin WangK. Sreekumaran NairAngela DispenzieriSrinivasa R. Nagalla
- Partner nations
- United StatesIndiaCanada
In The Last Decade
Surendra Dasari
231 papers receiving 8.1k citations
Hit Papers
Peers
Comparison fields: 5 of 155
- Cancer Research 1.3k
- Nephrology 617
- Molecular Biology 5.2k
- Physiology 1.7k
- Hematology 635
Countries citing papers authored by Surendra Dasari
This map shows the geographic impact of Surendra Dasari'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 Surendra Dasari with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Surendra Dasari more than expected).
Fields of papers citing papers by Surendra Dasari
This network shows the impact of papers produced by Surendra Dasari. 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 Surendra Dasari. The network helps show where Surendra Dasari may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Surendra Dasari, 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 | 2 | |
| 2 | 2025 | 1 | |
| 3 | 2025 | 2 | |
| 4 | 2025 | 0 | |
| 5 | 2024 | 1 | |
| 6 | 2024 | 1 | |
| 7 | 2024 | 8 | |
| 8 | 2024 | 14 | |
| 9 | 2024 | 0 | |
| 10 | 2023 | 6 | |
| 11 | 2023 | 15 | |
| 12 | 2023 | 5 | |
| 13 | 2023 | 11 | |
| 14 | 2023 | 10 | |
| 15 | 2022 | 0 | |
| 16 | 2021 | 13 | |
| 17 | 2019 | 56 | |
| 18 | 2017 | 71 | |
| 19 | 2016 | 106 | |
| 20 | 2016 | 47 |
About Surendra Dasari
Surendra Dasari is a scholar working on Nephrology, Hematology, Molecular Biology, Physiology and Cell Biology, having authored 252 papers that have together received 8.2k indexed citations. Recurring topics across this work include Amyloidosis: Diagnosis, Treatment, Outcomes (70 papers), Adipose Tissue and Metabolism (25 papers), Multiple Myeloma Research and Treatments (22 papers), Advanced Proteomics Techniques and Applications (18 papers), Muscle metabolism and nutrition (16 papers), Renal Diseases and Glomerulopathies (16 papers), Mass Spectrometry Techniques and Applications (14 papers) and Monoclonal and Polyclonal Antibodies Research (14 papers). The work is most often cited by research in Cancer Research (1.3k citations), Nephrology (617 citations), Molecular Biology (5.2k citations), Physiology (1.7k citations) and Hematology (635 citations). Surendra Dasari has collaborated with scholars based in United States, India and Canada. Frequent co-authors include Jean‐Pierre Kocher, Liguo Wang, Hyun Jung Park, Wei Li, Shengqin Wang, K. Sreekumaran Nair, Angela Dispenzieri, Srinivasa R. Nagalla, Ian R. Lanza and Paul J. Kurtin. Their work appears in journals such as Journal of Proteome Research, Blood, Human Pathology, Kidney International and Amyloid.
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.