Nageshwar Budha
- Pharmacology top 2%
- Pharmacogenetics and Drug Metabolism 7
- Oncology top 5%
- Cancer Immunotherapy and Biomarkers 12
- CAR-T cell therapy research 9
- Drug Transport and Resistance Mechanisms 7
- Pharmaceutical Science top 5%
- Genetics top 10%
- Hematology top 10%
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- Lipoproteins and Cardiovascular Health 7
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- PI3K/AKT/mTOR signaling in cancer 7
- Cancer therapeutics and mechanisms 5
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- Biosimilars and Bioanalytical Methods 5
- Co-authors
- Mark J. DresserBernd MeibohmLeslie Z. BenetAdam FrymoyerScott N. HoldenJin Y. JinJ. A. WareRichard Lee
- Partner nations
- United StatesChinaAustralia
In The Last Decade
Nageshwar Budha
51 papers receiving 1.4k citations
Peers
Comparison fields: 5 of 111
- Pharmacology 189
- Oncology 477
- Pharmaceutical Science 97
- Genetics 117
- Hematology 118
Countries citing papers authored by Nageshwar Budha
This map shows the geographic impact of Nageshwar Budha'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 Nageshwar Budha with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Nageshwar Budha more than expected).
Fields of papers citing papers by Nageshwar Budha
This network shows the impact of papers produced by Nageshwar Budha. 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 Nageshwar Budha. The network helps show where Nageshwar Budha may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Nageshwar Budha, 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 | 0 | |
| 2 | 2025 | 3 | |
| 3 | 2024 | 6 | |
| 4 | 2024 | 3 | |
| 5 | 2023 | 10 | |
| 6 | 2021 | 4 | |
| 7 | 2020 | 1 | |
| 8 | 2019 | 1 | |
| 9 | 2017 | 44 | |
| 10 | 2016 | 31 | |
| 11 | 2015 | 15 | |
| 12 | 2015 | 22 | |
| 13 | 2014 | 8 | |
| 14 | Abstract 12009: Effect of RG7652, a mAb Against PCSK9, on Apolipoprotein B, Oxidized LDL, Lipoprotein(a) and Lipoprotein-Associated Phospholipase A2 in Healthy Individuals With Elevated LDL-c | 2013 | 2 |
| 15 | 2012 | 13 | |
| 16 | 2011 | 8 | |
| 17 | 2009 | 28 | |
| 18 | 2008 | 29 | |
| 19 | 2008 | 34 | |
| 20 | 2007 | 84 |
About Nageshwar Budha
Nageshwar Budha is a scholar working on Oncology, Pharmacology and Immunology, having authored 52 papers that have together received 1.5k indexed citations. Recurring topics across this work include Cancer Immunotherapy and Biomarkers (12 papers), CAR-T cell therapy research (9 papers), Pharmacogenetics and Drug Metabolism (7 papers), Lipoproteins and Cardiovascular Health (7 papers), PI3K/AKT/mTOR signaling in cancer (7 papers), Drug Transport and Resistance Mechanisms (7 papers), Cancer therapeutics and mechanisms (5 papers) and Biosimilars and Bioanalytical Methods (5 papers). The work is most often cited by research in Pharmacology (189 citations), Oncology (477 citations) and Pharmaceutical Science (97 citations). Nageshwar Budha has collaborated with scholars based in United States, China and Australia. Frequent co-authors include Mark J. Dresser, Bernd Meibohm, Leslie Z. Benet, Adam Frymoyer, Scott N. Holden, Jin Y. Jin, J. A. Ware, Richard Lee, Nitin Mehrotra and Srikumar Sahasranaman. Their work appears in journals such as Circulation, Journal of Clinical Oncology and Blood.
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.