Foo Cheung
Impact in
- Aging top 5%
- Genetics, Aging, and Longevity in Model Organisms
- Immunology top 10%
- Immune Cell Function and Interaction
- T-cell and B-cell Immunology
Papers in
- Immunology 12
- T-cell and B-cell Immunology 5
- Immune Cell Function and Interaction 4
- Immunotherapy and Immune Responses 3
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- Single-cell and spatial transcriptomics 2
- Co-authors
- Angélique Biancotto (14 shared papers)Julián Candia (9 shared papers)Giovanna Fantoni (7 shared papers)Yuri Kotliarov (10 shared papers)Jinguo Chen (11 shared papers)John S. Tsang (9 shared papers)Miguel A. Aon (1 shared paper)Marta González‐Freire (1 shared paper)
- Journals
- Journal of Translational Medicine (3 papers)Scientific Reports (2 papers)Nature Medicine (2 papers)Immunity (2 papers)JCI Insight (2 papers)
- Partner nations
- United StatesUnited KingdomChina
In The Last Decade
Foo Cheung
24 papers receiving 1.3k citations
Foo Cheung's Hit Papers
Peers
Comparison fields: 5 of 106
- Aging 75
- Immunology 350
- Rheumatology 189
- Physiology 292
- Biological Psychiatry 25
Countries citing papers authored by Foo Cheung
This map shows the geographic impact of Foo Cheung'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 Foo Cheung with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Foo Cheung more than expected).
Fields of papers citing papers by Foo Cheung
This network shows the impact of papers produced by Foo Cheung. 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 Foo Cheung. The network helps show where Foo Cheung may publish in the future.
Co-authors
The 25 scholars most cited alongside Foo Cheung, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 25 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | Plasma proteomic signature of age in healthy humans Hit paper breakdown → | 2018 | 339 |
| 2 | 2017 | 236 | |
| 3 | 2016 | 122 | |
| 4 | 2020 | 98 | |
| 5 | 2018 | 89 | |
| 6 | 2020 | 43 | |
| 7 | 2024 | 41 | |
| 8 | 2020 | 38 | |
| 9 | 2017 | 36 | |
| 10 | 1999 | 34 | |
| 11 | 2016 | 33 | |
| 12 | 2018 | 33 | |
| 13 | 1997 | 21 | |
| 14 | 2020 | 19 | |
| 15 | 2018 | 19 | |
| 16 | 2019 | 18 | |
| 17 | 2017 | 15 | |
| 18 | 2018 | 15 | |
| 19 | 2021 | 15 | |
| 20 | 2023 | 14 |
About Foo Cheung
Foo Cheung is a scholar working on Immunology, Molecular Biology, Rheumatology, Pulmonary and Respiratory Medicine and Oncology, having authored 25 papers that have together received 1.3k indexed citations. Recurring topics across this work include T-cell and B-cell Immunology (5 papers), Immune Cell Function and Interaction (4 papers), Immunotherapy and Immune Responses (3 papers), Single-cell and spatial transcriptomics (2 papers), Acute Myeloid Leukemia Research (2 papers), Hematopoietic Stem Cell Transplantation (2 papers), SARS-CoV-2 and COVID-19 Research (2 papers) and Advanced Proteomics Techniques and Applications (2 papers). The work is most often cited by research in Aging (75 citations), Immunology (350 citations), Rheumatology (189 citations), Physiology (292 citations) and Biological Psychiatry (25 citations). Foo Cheung has collaborated with scholars based in United States, United Kingdom and China. Frequent co-authors include Angélique Biancotto, Julián Candia, Giovanna Fantoni, Yuri Kotliarov, Jinguo Chen, John S. Tsang, Miguel A. Aon, Marta González‐Freire, Luigi Ferrucci and Toshiko Tanaka. Their work appears in journals such as Journal of Translational Medicine, Scientific Reports, Nature Medicine, Immunity and JCI Insight.
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.