Vaiva Vezys
- Immunology top 0.1%
- Immune Cell Function and Interaction 44
- T-cell and B-cell Immunology 43
- Immunotherapy and Immune Responses 41
- Immune Response and Inflammation 6
- Virology top 2%
- Oncology top 2%
- CAR-T cell therapy research 7
- Cancer Immunotherapy and Biomarkers 6
- Neurology top 2%
- Infectious Diseases top 2%
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- Single-cell and spatial transcriptomics 5
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- Diabetes and associated disorders 5
- Co-authors
- David MasopustLeo LefrançoisAmanda L. MarzoJason M. SchenkelKathryn FraserLalit K. BeuraRafi AhmedDaniel L. Barber
- Cited by
- ImmunologyVirologyOncology
- Journals
- Nature (6 papers)Science (2 papers)Proceedings of the National Academy of Sciences (2 papers)
- Partner nations
- United StatesAustraliaUnited Kingdom
In The Last Decade
Vaiva Vezys
72 papers receiving 9.1k citations
Hit Papers
Peers
Comparison fields: 5 of 115
- Immunology 7.7k
- Virology 332
- Oncology 1.5k
- Neurology 358
- Infectious Diseases 776
Countries citing papers authored by Vaiva Vezys
This map shows the geographic impact of Vaiva Vezys'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 Vaiva Vezys with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Vaiva Vezys more than expected).
Fields of papers citing papers by Vaiva Vezys
This network shows the impact of papers produced by Vaiva Vezys. 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 Vaiva Vezys. The network helps show where Vaiva Vezys may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Vaiva Vezys, 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 | 3 | |
| 2 | 2024 | 15 | |
| 3 | 2024 | 3 | |
| 4 | 2023 | 14 | |
| 5 | Functional T cells are capable of supernumerary cell division and longevitybreakdown → | 2023 | 111 |
| 6 | 2023 | 25 | |
| 7 | 2022 | 3 | |
| 8 | 2022 | 45 | |
| 9 | 2021 | 102 | |
| 10 | 2019 | 140 | |
| 11 | Normalizing the environment recapitulates adult human immune traits in laboratory micebreakdown → | 2016 | 760 |
| 12 | 2015 | 37 | |
| 13 | Resident memory CD8 T cells trigger protective innate and adaptive immune responsesbreakdown → | 2014 | 545 |
| 14 | 2014 | 23 | |
| 15 | 2006 | 294 | |
| 16 | 2006 | 160 | |
| 17 | 2005 | 65 | |
| 18 | 2004 | 106 | |
| 19 | 2002 | 52 | |
| 20 | 2002 | 9 |
About Vaiva Vezys
Vaiva Vezys is a scholar working on Immunology, Oncology and Genetics, having authored 73 papers that have together received 9.2k indexed citations. Recurring topics across this work include Immune Cell Function and Interaction (44 papers), T-cell and B-cell Immunology (43 papers), Immunotherapy and Immune Responses (41 papers), CAR-T cell therapy research (7 papers), Cancer Immunotherapy and Biomarkers (6 papers), Immune Response and Inflammation (6 papers), Single-cell and spatial transcriptomics (5 papers) and Diabetes and associated disorders (5 papers). The work is most often cited by research in Immunology (7.7k citations), Virology (332 citations) and Oncology (1.5k citations). Vaiva Vezys has collaborated with scholars based in United States, Australia and United Kingdom. Frequent co-authors include David Masopust, Leo Lefrançois, Amanda L. Marzo, Jason M. Schenkel, Kathryn Fraser, Lalit K. Beura, Rafi Ahmed, Daniel L. Barber, Kerry A. Casey and E. John Wherry. Their work appears in journals such as Nature, Science and Proceedings of the National Academy of Sciences.
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.