Pranali Ravikumar
Impact in
- Oncology top 10%
- CAR-T cell therapy research
-
- Immunotherapy and Immune Responses
- Immune Cell Function and Interaction
Papers in
- Oncology 7
- CAR-T cell therapy research 7
-
- Viral Infectious Diseases and Gene Expression in Insects 2
- Co-authors
- Carl H. June (4 shared papers)Margaret M. Billingsley (1 shared paper)Nathan Singh (2 shared papers)Michael J. Mitchell (1 shared paper)Rui Zhang (1 shared paper)Austin K. Rennels (1 shared paper)Sangya Agarwal (2 shared papers)Tong Da (2 shared papers)
- Journals
- Cancer Research (1 paper)Nano Letters (1 paper)Virus Genes (1 paper)Blood (1 paper)The Journal of Immunology (1 paper)
- Partner nations
- United StatesIndiaSouth Africa
In The Last Decade
Pranali Ravikumar
11 papers receiving 677 citations
Pranali Ravikumar's Hit Papers
Peers
Comparison fields: 5 of 54
- Oncology 311
- Immunology 184
- Molecular Biology 408
- Genetics 138
- Biomaterials 53
Countries citing papers authored by Pranali Ravikumar
This map shows the geographic impact of Pranali Ravikumar'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 Pranali Ravikumar with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Pranali Ravikumar more than expected).
Fields of papers citing papers by Pranali Ravikumar
This network shows the impact of papers produced by Pranali Ravikumar. 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 Pranali Ravikumar. The network helps show where Pranali Ravikumar may publish in the future.
Co-authors
The 25 scholars most cited alongside Pranali Ravikumar, 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 | Ionizable Lipid Nanoparticle-Mediated mRNA Delivery for Human CAR T Cell Engineering Hit paper breakdown → | 2020 | 488 |
| 2 | Deletion of the inhibitory co-receptor CTLA-4 enhances and invigorates chimeric antigen receptor T cells Hit paper breakdown → | 2023 | 118 |
| 3 | 2020 | 38 | |
| 4 | 2010 | 16 | |
| 5 | 2020 | 8 | |
| 6 | 2008 | 5 | |
| 7 | 2011 | 5 | |
| 8 | 2011 | 3 | |
| 9 | 2022 | 2 | |
| 10 | 2018 | 1 | |
| 11 | 2018 | 1 | |
| 12 | 2020 | 1 | |
| 13 | 2014 | 0 |
About Pranali Ravikumar
Pranali Ravikumar is a scholar working on Oncology, Molecular Biology, Agronomy and Crop Science, Cardiology and Cardiovascular Medicine and Genetics, having authored 13 papers that have together received 686 indexed citations. Recurring topics across this work include CAR-T cell therapy research (7 papers), Animal Disease Management and Epidemiology (4 papers), Viral Infections and Immunology Research (3 papers), Virus-based gene therapy research (3 papers), Viral Infectious Diseases and Gene Expression in Insects (2 papers), Immune Cell Function and Interaction (2 papers), Mass Spectrometry Techniques and Applications (1 paper) and Immunotherapy and Immune Responses (1 paper). The work is most often cited by research in Oncology (311 citations), Immunology (184 citations), Molecular Biology (408 citations), Genetics (138 citations) and Biomaterials (53 citations). Pranali Ravikumar has collaborated with scholars based in United States, India and South Africa. Frequent co-authors include Carl H. June, Margaret M. Billingsley, Nathan Singh, Michael J. Mitchell, Rui Zhang, Austin K. Rennels, Sangya Agarwal, Tong Da, January Salas-McKee and Gabriela Plesa. Their work appears in journals such as Cancer Research, Nano Letters, Virus Genes, Blood and The Journal of Immunology.
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.