Vikas A. Gupta
Impact in
- Hematology top 1%
- Multiple Myeloma Research and Treatments
- Oncology top 5%
- Peptidase Inhibition and Analysis
- CAR-T cell therapy research
Papers in
- Hematology 61
- Multiple Myeloma Research and Treatments 55
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- Protein Degradation and Inhibitors 17
- Cell death mechanisms and regulation 8
- Co-authors
- Lawrence Boise (43 shared papers)Sagar Lonial (54 shared papers)Jonathan L. Kaufman (46 shared papers)Ajay K. Nooka (52 shared papers)Craig C. Hofmeister (41 shared papers)Nisha S. Joseph (39 shared papers)Benjamin G. Barwick (15 shared papers)Madhav V. Dhodapkar (33 shared papers)
- Journals
- Blood (32 papers)Journal of Clinical Oncology (7 papers)Cancer (3 papers)Blood Cancer Journal (2 papers)Haematologica (2 papers)
- Partner nations
- United StatesCanadaIndia
In The Last Decade
Vikas A. Gupta
73 papers receiving 1.7k citations
Peers
Comparison fields: 5 of 69
- Hematology 914
- Oncology 564
- Genetics 171
- Molecular Biology 887
- Neurology 172
Countries citing papers authored by Vikas A. Gupta
This map shows the geographic impact of Vikas A. Gupta'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 Vikas A. Gupta with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Vikas A. Gupta more than expected).
Fields of papers citing papers by Vikas A. Gupta
This network shows the impact of papers produced by Vikas A. Gupta. 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 Vikas A. Gupta. The network helps show where Vikas A. Gupta may publish in the future.
Co-authors
The 25 scholars most cited alongside Vikas A. Gupta, 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 78 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2001 | 280 | |
| 2 | 2020 | 137 | |
| 3 | 2019 | 118 | |
| 4 | 2019 | 115 | |
| 5 | 2019 | 113 | |
| 6 | 2015 | 101 | |
| 7 | 2022 | 97 | |
| 8 | 2019 | 96 | |
| 9 | 2017 | 85 | |
| 10 | 2020 | 77 | |
| 11 | 2019 | 65 | |
| 12 | 2021 | 56 | |
| 13 | 2005 | 46 | |
| 14 | 2018 | 34 | |
| 15 | 2021 | 20 | |
| 16 | 2019 | 20 | |
| 17 | 2016 | 19 | |
| 18 | 2021 | 17 | |
| 19 | 2022 | 12 | |
| 20 | 2021 | 11 |
About Vikas A. Gupta
Vikas A. Gupta is a scholar working on Hematology, Molecular Biology, Oncology, Genetics and Radiology, Nuclear Medicine and Imaging, having authored 78 papers that have together received 1.7k indexed citations. Recurring topics across this work include Multiple Myeloma Research and Treatments (55 papers), Protein Degradation and Inhibitors (17 papers), Cell death mechanisms and regulation (8 papers), Cancer Treatment and Pharmacology (8 papers), Monoclonal and Polyclonal Antibodies Research (8 papers), CAR-T cell therapy research (8 papers), Cancer Mechanisms and Therapy (7 papers) and Chronic Lymphocytic Leukemia Research (7 papers). The work is most often cited by research in Hematology (914 citations), Oncology (564 citations), Genetics (171 citations), Molecular Biology (887 citations) and Neurology (172 citations). Vikas A. Gupta has collaborated with scholars based in United States, Canada and India. Frequent co-authors include Lawrence Boise, Sagar Lonial, Jonathan L. Kaufman, Ajay K. Nooka, Craig C. Hofmeister, Nisha S. Joseph, Benjamin G. Barwick, Madhav V. Dhodapkar, Shannon M. Matulis and Paula M. Vertino. Their work appears in journals such as Blood, Journal of Clinical Oncology, Cancer, Blood Cancer Journal and Haematologica.
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.