Foo Cheung

3.7k total citations · 1 hit paper
25 papers, 1.3k citations indexed

About

Foo Cheung is a scholar working on Immunology, Molecular Biology and Rheumatology. According to data from OpenAlex, Foo Cheung has authored 25 papers receiving a total of 1.3k indexed citations (citations by other indexed papers that have themselves been cited), including 12 papers in Immunology, 9 papers in Molecular Biology and 4 papers in Rheumatology. Recurrent topics in Foo Cheung's work include T-cell and B-cell Immunology (5 papers), Immune Cell Function and Interaction (4 papers) and Immunotherapy and Immune Responses (3 papers). Foo Cheung is often cited by papers focused on T-cell and B-cell Immunology (5 papers), Immune Cell Function and Interaction (4 papers) and Immunotherapy and Immune Responses (3 papers). Foo Cheung collaborates with scholars based in United States, United Kingdom and China. Foo Cheung's co-authors include Angélique Biancotto, Julián Candia, Giovanna Fantoni, Yuri Kotliarov, Jinguo Chen, John S. Tsang, Ruin Moaddel, Miguel A. Aon, Toshiko Tanaka and Luigi Ferrucci and has published in prestigious journals such as Nature Medicine, Blood and Immunity.

In The Last Decade

Foo Cheung

24 papers receiving 1.3k citations

Hit Papers

Plasma proteomic signature of age in healthy humans 2018 2026 2020 2023 2018 100 200 300

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Foo Cheung United States 16 563 350 292 189 148 25 1.3k
Johan Björkesten Sweden 7 476 0.8× 257 0.7× 190 0.7× 120 0.6× 189 1.3× 8 1.5k
Vicky L. Morrison United Kingdom 14 394 0.7× 444 1.3× 132 0.5× 53 0.3× 129 0.9× 20 1.1k
Kausik Mandal India 22 634 1.1× 337 1.0× 109 0.4× 92 0.5× 147 1.0× 114 1.7k
Demetrios A. Arvanitis Greece 25 776 1.4× 194 0.6× 155 0.5× 138 0.7× 163 1.1× 63 1.7k
Christine Modoux Switzerland 10 182 0.3× 302 0.9× 101 0.3× 198 1.0× 130 0.9× 10 896
Galina A. Gusarova United States 21 1.5k 2.7× 526 1.5× 185 0.6× 34 0.2× 257 1.7× 41 2.6k
Daniel Ekman Sweden 4 370 0.7× 220 0.6× 154 0.5× 107 0.6× 162 1.1× 4 1.2k
Bernhardt Zeiher United States 16 595 1.1× 230 0.7× 119 0.4× 65 0.3× 284 1.9× 35 1.7k
Roman‐Ulrich Müller Germany 22 903 1.6× 81 0.2× 280 1.0× 47 0.2× 122 0.8× 96 1.7k
Sho Takagi Japan 20 243 0.4× 282 0.8× 223 0.8× 66 0.3× 433 2.9× 62 1.4k

Countries citing papers authored by Foo Cheung

Since Specialization
Citations

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

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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-authorship network of co-authors of Foo Cheung

This figure shows the co-authorship network connecting the top 25 collaborators of Foo Cheung. A scholar is included among the top collaborators of Foo Cheung based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Foo Cheung. Foo Cheung is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Mulè, Matthew P., Andrew J. Martins, Foo Cheung, et al.. (2024). Integrating population and single-cell variations in vaccine responses identifies a naturally adjuvanted human immune setpoint. Immunity. 57(5). 1160–1176.e7. 8 indexed citations
2.
Assis, Felipe Lopes de, Kenneth B. Hoehn, Xiaozhen Zhang, et al.. (2023). Tracking B cell responses to the SARS-CoV-2 mRNA-1273 vaccine. Cell Reports. 42(7). 112780–112780. 14 indexed citations
3.
Gordon‐Lipkin, Eliza, Foo Cheung, Jinguo Chen, et al.. (2023). Inflammatory and interferon gene expression signatures in patients with mitochondrial disease. Journal of Translational Medicine. 21(1). 331–331. 13 indexed citations
4.
Cheung, Foo, Richard Apps, Lesia Dropulic, et al.. (2022). Sex and prior exposure jointly shape innate immune responses to a live herpesvirus vaccine. eLife. 12. 6 indexed citations
5.
Han, Kim, Komudi Singh, Shahin Hassanzadeh, et al.. (2021). Identification and Validation of Nutrient State-Dependent Serum Protein Mediators of Human CD4+ T Cell Responsiveness. Nutrients. 13(5). 1492–1492. 15 indexed citations
6.
Çelik, Haydar, Katherine E. Lindblad, Bogdan Popescu, et al.. (2020). Highly multiplexed proteomic assessment of human bone marrow in acute myeloid leukemia. Blood Advances. 4(2). 367–379. 38 indexed citations
7.
Demidowich, Andrew P., J Levine, Richard Apps, et al.. (2020). Colchicine’s effects on metabolic and inflammatory molecules in adults with obesity and metabolic syndrome: results from a pilot randomized controlled trial. International Journal of Obesity. 44(8). 1793–1799. 43 indexed citations
8.
Apps, Richard, Yuri Kotliarov, Foo Cheung, et al.. (2020). Multimodal immune phenotyping of maternal peripheral blood in normal human pregnancy. JCI Insight. 5(7). 19 indexed citations
9.
Karmaus, Peer W. F., Min Shi, Shira Perl, et al.. (2019). Effects of rosuvastatin on the immune system in healthy volunteers with normal serum cholesterol. JCI Insight. 4(21). 18 indexed citations
10.
Çelik, Haydar, Katherine E. Lindblad, Bogdan Popescu, et al.. (2019). A Novel Proteomic Profiling of the Bone Marrow Microenvironment Reveals Elevated Levels of the Chemokine CCL23 Isoforms in Acute Myeloid Leukemia. Blood. 134(Supplement_1). 2709–2709.
11.
Giudice, Valentina, Zhijie Wu, Sachiko Kajigaya, et al.. (2018). Circulating S100A8 and S100A9 protein levels in plasma of patients with acquired aplastic anemia and myelodysplastic syndromes. Cytokine. 113. 462–465. 33 indexed citations
12.
Chen, Jinguo, et al.. (2018). PBMC fixation and processing for Chromium single-cell RNA sequencing. Journal of Translational Medicine. 16(1). 198–198. 89 indexed citations
13.
Tanaka, Toshiko, Angélique Biancotto, Ruin Moaddel, et al.. (2018). Plasma proteomic signature of age in healthy humans. Aging Cell. 17(5). e12799–e12799. 339 indexed citations breakdown →
14.
El‐Chemaly, Souheil, Foo Cheung, Yuri Kotliarov, et al.. (2018). The Immunome in Two Inherited Forms of Pulmonary Fibrosis. Frontiers in Immunology. 9. 76–76. 19 indexed citations
15.
Candia, Julián, Foo Cheung, Yuri Kotliarov, et al.. (2017). Assessment of Variability in the SOMAscan Assay. Scientific Reports. 7(1). 236 indexed citations
16.
Cheung, Foo, Giovanna Fantoni, Brian A. Sellers, et al.. (2017). Web Tool for Navigating and Plotting SomaLogic ADAT Files. Journal of Open Research Software. 5(1). 20–20. 15 indexed citations
17.
Goswami, Meghali, Gabrielle T. Prince, Angélique Biancotto, et al.. (2017). Impaired B cell immunity in acute myeloid leukemia patients after chemotherapy. Journal of Translational Medicine. 15(1). 155–155. 36 indexed citations
18.
Lu, Yong, Angélique Biancotto, Foo Cheung, et al.. (2016). Systematic Analysis of Cell-to-Cell Expression Variation of T Lymphocytes in a Human Cohort Identifies Aging and Genetic Associations. Immunity. 45(5). 1162–1175. 33 indexed citations
19.
Olnes, Matthew J., Yuri Kotliarov, Angélique Biancotto, et al.. (2016). Effects of Systemically Administered Hydrocortisone on the Human Immunome. Scientific Reports. 6(1). 23002–23002. 122 indexed citations
20.
Lam, Alfred K., et al.. (1997). Atypical manifestations in a patient with systemic lupus erythematosus.. Journal of Clinical Pathology. 50(2). 174–176. 21 indexed citations

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.

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