Nina Le Bert

7.6k citations
42 papers · 3.4k indexed · 2 hit papers · h-index 23

Impact in

Papers in

Nina Le Bert

41 papers receiving 3.3k citations

Hit Papers

Early induction of functional SARS-CoV-2-specific T cells associates with rapid viral clearance and mild disease in COVID-19 patients 2021 · 440 citations
44020202026202220244008001.2k

Peers

Nina Le Bert
Comparison fields: 5 of 102
  • Infectious Diseases 2.2k
  • Hepatology 445
  • Immunology 1.1k
  • Modeling and Simulation 219
  • Neurology 458
Replace Adeline Chia with:
Adeline Chia Singapore
Anthony T. Tan Singapore
Kamini Kunasegaran Singapore
C Tham Singapore
Min Wu China
Christiane S. Eberhardt Switzerland
Chiara Agrati Italy
Jieliang Chen China
Orna Mor Israel
Yan Guo China
Nina Le Bert relative to Adeline Chia Singapore Adeline Chia's profile →
Citations per field
00.5×1.7×
Adeline Chia · 1×
Citations per year

Countries citing papers authored by Nina Le Bert

Since Specialization
Citations

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

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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.

Border = papers with Nina Le Bert Line = papers co-authored together Nina Le Bert links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 20250
2 20252
3 202410
4 202426
5 20232
6 20233
7 202272
8 202212
9 202264
10 202221
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 →
2021440
12 202172
13 2021101
14 2021103
15 2020108
16
SARS-CoV-2-specific T cell immunity in cases of COVID-19 and SARS, and uninfected controls
Hit paper breakdown →
20201224
17 2018198
18 201418
19 2014128
20 201417

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.

Explore authors with similar magnitude of impact

Rankless by CCL
2026