Ying K. Tam
- Molecular Biology top 0.5%
- Immunology top 0.5%
- Infectious Diseases top 0.5%
- Genetics top 1%
- Oncology top 5%
- Co-authors
- Barbara L. MuiPieter R. CullisMichael J. HopeThomas D. MaddenPaulo J.C. LinDrew WeissmanNorbert PardiSam Chen
- Topics
- RNA Interference and Gene Delivery (53 papers)Immunotherapy and Immune Responses (31 papers)Immune Cell Function and Interaction (18 papers)
- Partner nations
- United StatesCanadaGermany
In The Last Decade
Ying K. Tam
104 papers receiving 9.1k citations
Hit Papers
Peers
Comparison fields: 5 of 133
- Molecular Biology 6.5k
- Immunology 2.5k
- Infectious Diseases 1.8k
- Genetics 1.2k
- Oncology 894
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 of co-authors of Ying K. Tam
This figure shows the co-authorship network connecting the top 25 collaborators of Ying K. Tam. A scholar is included among the top collaborators of Ying K. Tam 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 Ying K. Tam. Ying K. Tam is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 11 | |
| 3 | 4 | |
| 4 | 1 | |
| 5 | 0 | |
| 6 | 24 | |
| 7 | Development of an mRNA-lipid nanoparticle vaccine against Lyme diseasebreakdown → | 46 |
| 8 | 1 | |
| 9 | 72 | |
| 10 | 57 | |
| 11 | 42 | |
| 12 | 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 → | 154 |
| 14 | 36 | |
| 15 | 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 | 2 |
| 17 | 5 | |
| 18 | 1 | |
| 19 | 214 | |
| 20 | 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) and Immune Cell Function and Interaction (18 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.