Ying K. Tam
- Immunology top 0.5%
- Immunotherapy and Immune Responses 31
- Immune Cell Function and Interaction 18
- Immune Response and Inflammation 11
- Infectious Diseases top 0.5%
- SARS-CoV-2 and COVID-19 Research 15
- Molecular Biology top 0.5%
- RNA Interference and Gene Delivery 53
- Advanced biosensing and bioanalysis techniques 17
- Biomaterials top 1%
- Animal Science and Zoology top 0.5%
- Animal Virus Infections Studies 9
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- Virus-based gene therapy research 13
Ying K. Tam
104 papers receiving 9.1k citations
Hit Papers
Peers
Comparison fields: 5 of 133
- Immunology 2.5k
- Infectious Diseases 1.8k
- Molecular Biology 6.5k
- Biomaterials 836
- Animal Science and Zoology 622
Countries citing papers authored by Ying K. Tam
This map shows the geographic impact of Ying K. Tam'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 Ying K. Tam with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ying K. Tam more than expected).
Fields of papers citing papers by Ying K. Tam
This network shows the impact of papers produced by Ying K. Tam. 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 Ying K. Tam. The network helps show where Ying K. Tam may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Ying K. Tam, 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 | 1 | |
| 2 | 2025 | 11 | |
| 3 | 2024 | 4 | |
| 4 | 2024 | 1 | |
| 5 | 2024 | 0 | |
| 6 | 2024 | 24 | |
| 7 | Development of an mRNA-lipid nanoparticle vaccine against Lyme diseasebreakdown → | 2023 | 46 |
| 8 | 2023 | 1 | |
| 9 | 2023 | 72 | |
| 10 | 2022 | 57 | |
| 11 | 2021 | 42 | |
| 12 | 2021 | 13 | |
| 13 | PECAM-1 directed re-targeting of exogenous mRNA providing two orders of magnitude enhancement of vascular delivery and expression in lungs independent of apolipoprotein E-mediated uptakebreakdown → | 2018 | 154 |
| 14 | 2012 | 36 | |
| 15 | 2010 | 33 | |
| 16 | Lipid encapsulation promotes co-localization of methylated CpG ODN and TLR9 in late endosomes: A new model for the immunostimulatory activity of CpG DNA | 2008 | 2 |
| 17 | 2008 | 5 | |
| 18 | 2003 | 1 | |
| 19 | 2001 | 214 | |
| 20 | 1999 | 106 |
About Ying K. Tam
Ying K. Tam is a scholar working on Immunology, Virology and Infectious Diseases, having authored 107 papers that have together received 9.3k indexed citations. Recurring topics across this work include RNA Interference and Gene Delivery (53 papers), Immunotherapy and Immune Responses (31 papers), Immune Cell Function and Interaction (18 papers), Advanced biosensing and bioanalysis techniques (17 papers), SARS-CoV-2 and COVID-19 Research (15 papers), Virus-based gene therapy research (13 papers), Immune Response and Inflammation (11 papers) and Animal Virus Infections Studies (9 papers). The work is most often cited by research in Immunology (2.5k citations), Infectious Diseases (1.8k citations) and Molecular Biology (6.5k citations). Ying K. Tam has collaborated with scholars based in United States, Canada and Germany. Frequent co-authors include Barbara L. Mui, Pieter R. Cullis, Michael J. Hope, Thomas D. Madden, Paulo J.C. Lin, Drew Weissman, Norbert Pardi, Sam Chen, Akin Akinc and Steven M. Ansell. Their work appears in journals such as Nature, Science and Proceedings of the National Academy of Sciences.
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.