Nina Le Bert
Impact in
- Infectious Diseases top 0.5%
- SARS-CoV-2 and COVID-19 Research
- COVID-19 Clinical Research Studies
- Hepatology top 2%
- Hepatitis C virus research
Papers in
-
- SARS-CoV-2 and COVID-19 Research 21
- COVID-19 Clinical Research Studies 19
-
- Hepatitis C virus research 9
- Co-authors
- Antonio BertolettiAnthony T. TanJenny G. LowKamini KunasegaranAdeline ChiaC ThamShirin KalimuddinLin‐Fa Wang
- Journals
- Journal of Hepatology (6 papers)Journal of Clinical Investigation (4 papers)Cellular and Molecular Immunology (3 papers)Nature Medicine (2 papers)Cell Reports (2 papers)
- Partner nations
- SingaporeUnited KingdomUnited States
In The Last Decade
Nina Le Bert
41 papers receiving 3.3k citations
Hit Papers
Peers
Comparison fields: 5 of 102
- Infectious Diseases 2.2k
- Hepatology 445
- Immunology 1.1k
- Modeling and Simulation 219
- Neurology 458
Countries citing papers authored by Nina Le Bert
This map shows the geographic impact of Nina Le Bert'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 Nina Le Bert with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Nina Le Bert more than expected).
Fields of papers citing papers by Nina Le Bert
This network shows the impact of papers produced by Nina Le Bert. 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 Nina Le Bert. The network helps show where Nina Le Bert may publish in the future.
Co-authors
The 25 scholars most cited alongside Nina Le Bert, 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 | 2 | |
| 3 | 2024 | 10 | |
| 4 | 2024 | 26 | |
| 5 | 2023 | 2 | |
| 6 | 2023 | 3 | |
| 7 | 2022 | 72 | |
| 8 | 2022 | 12 | |
| 9 | 2022 | 64 | |
| 10 | 2022 | 21 | |
| 11 | Early induction of functional SARS-CoV-2-specific T cells associates with rapid viral clearance and mild disease in COVID-19 patients Hit paper breakdown → | 2021 | 440 |
| 12 | 2021 | 72 | |
| 13 | 2021 | 101 | |
| 14 | 2021 | 103 | |
| 15 | 2020 | 108 | |
| 16 | SARS-CoV-2-specific T cell immunity in cases of COVID-19 and SARS, and uninfected controls Hit paper breakdown → | 2020 | 1224 |
| 17 | 2018 | 198 | |
| 18 | 2014 | 18 | |
| 19 | 2014 | 128 | |
| 20 | 2014 | 17 |
About Nina Le Bert
Nina Le Bert is a scholar working on Infectious Diseases, Hepatology, Immunology, Epidemiology and Health, having authored 42 papers that have together received 3.4k indexed citations. Recurring topics across this work include SARS-CoV-2 and COVID-19 Research (21 papers), COVID-19 Clinical Research Studies (19 papers), Hepatitis B Virus Studies (12 papers), Hepatitis C virus research (9 papers), CAR-T cell therapy research (6 papers), Immune Cell Function and Interaction (6 papers), Immunotherapy and Immune Responses (5 papers) and Long-Term Effects of COVID-19 (5 papers). The work is most often cited by research in Infectious Diseases (2.2k citations), Hepatology (445 citations), Immunology (1.1k citations), Modeling and Simulation (219 citations) and Neurology (458 citations). Nina Le Bert has collaborated with scholars based in Singapore, United Kingdom and United States. Frequent co-authors include Antonio Bertoletti, Anthony T. Tan, Jenny G. Low, Kamini Kunasegaran, Adeline Chia, C Tham, Shirin Kalimuddin, Lin‐Fa Wang, Wan Ni Chia and Martin Linster. Their work appears in journals such as Journal of Hepatology, Journal of Clinical Investigation, Cellular and Molecular Immunology, Nature Medicine and Cell Reports.
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.