Liat Dassa
Impact in
- Aging top 2%
- Genetics, Aging, and Longevity in Model Organisms
- Immunology top 5%
- Immune Cell Function and Interaction
- T-cell and B-cell Immunology
- Immunotherapy and Immune Responses
- Immune cells in cancer
Papers in
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- Immune Cell Function and Interaction 5
- T-cell and B-cell Immunology 3
- interferon and immune responses 1
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- Cytomegalovirus and herpesvirus research 4
- Co-authors
- Ofer Mandelboim (6 shared papers)Amit Novik (1 shared paper)Noa Stanietsky (1 shared paper)Ofer Levy (1 shared paper)Noam Stern‐Ginossar (1 shared paper)Stipan Jonjić (1 shared paper)Zurit Levine (1 shared paper)Hrvoje Šimić (1 shared paper)
- Journals
- Nature Communications (2 papers)Proceedings of the National Academy of Sciences (1 paper)The Journal of Cell Biology (1 paper)Journal of Virology (1 paper)PLoS Pathogens (1 paper)
- Partner nations
- IsraelGermanyUnited States
In The Last Decade
Liat Dassa
7 papers receiving 3.4k citations
Liat Dassa's Hit Papers
Peers
Comparison fields: 5 of 213
- Aging 110
- Immunology 857
- Physiology 534
- Oncology 544
- Molecular Biology 808
Countries citing papers authored by Liat Dassa
This map shows the geographic impact of Liat Dassa'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 Liat Dassa with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Liat Dassa more than expected).
Fields of papers citing papers by Liat Dassa
This network shows the impact of papers produced by Liat Dassa. 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 Liat Dassa. The network helps show where Liat Dassa may publish in the future.
Co-authors
The 25 scholars most cited alongside Liat Dassa, 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 | The interaction of TIGIT with PVR and PVRL2 inhibits human NK cell cytotoxicity Hit paper breakdown → | 2009 | 2718 |
| 2 | Directed elimination of senescent cells by inhibition of BCL-W and BCL-XL Hit paper breakdown → | 2016 | 761 |
| 3 | 2016 | 72 | |
| 4 | 2018 | 32 | |
| 5 | 2021 | 14 | |
| 6 | 2021 | 14 | |
| 7 | 2023 | 2 |
About Liat Dassa
Liat Dassa is a scholar working on Immunology, Epidemiology, Molecular Biology, Infectious Diseases and Oncology, having authored 7 papers that have together received 3.6k indexed citations. Recurring topics across this work include Immune Cell Function and Interaction (5 papers), Cytomegalovirus and herpesvirus research (4 papers), T-cell and B-cell Immunology (3 papers), interferon and immune responses (1 paper), RNA and protein synthesis mechanisms (1 paper), Autoimmune and Inflammatory Disorders Research (1 paper), Telomeres, Telomerase, and Senescence (1 paper) and Antifungal resistance and susceptibility (1 paper). The work is most often cited by research in Aging (110 citations), Immunology (857 citations), Physiology (534 citations), Oncology (544 citations) and Molecular Biology (808 citations). Liat Dassa has collaborated with scholars based in Israel, Germany and United States. Frequent co-authors include Ofer Mandelboim, Amit Novik, Noa Stanietsky, Ofer Levy, Noam Stern‐Ginossar, Stipan Jonjić, Zurit Levine, Hrvoje Šimić, Hagit Achdout and Jurica Arapović. Their work appears in journals such as Nature Communications, Proceedings of the National Academy of Sciences, The Journal of Cell Biology, Journal of Virology and PLoS Pathogens.
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.