Brent S. McKenzie
- Immunology top 0.05%
- Molecular Biology top 5%
- Genetics top 1%
- Oncology top 1%
- Epidemiology top 2%
- Co-authors
- J. DanielRobert A. KasteleinDan R. LittmanIvaylo I. IvanovCarlos E. TadokoroJuan J. LafailleLiang ZhouAlice Lepelley
- Topics
- T-cell and B-cell Immunology (12 papers)Immune Cell Function and Interaction (11 papers)IL-33, ST2, and ILC Pathways (9 papers)
- Partner nations
- AustraliaUnited KingdomUnited States
In The Last Decade
Brent S. McKenzie
44 papers receiving 12.3k citations
Hit Papers
Peers
Comparison fields: 5 of 126
- Immunology 9.6k
- Molecular Biology 2.0k
- Genetics 1.7k
- Oncology 1.7k
- Epidemiology 1.2k
Countries citing papers authored by Brent S. McKenzie
This map shows the geographic impact of Brent S. McKenzie'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 Brent S. McKenzie with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Brent S. McKenzie more than expected).
Fields of papers citing papers by Brent S. McKenzie
This network shows the impact of papers produced by Brent S. McKenzie. 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 Brent S. McKenzie. The network helps show where Brent S. McKenzie may publish in the future.
Co-authorship network of co-authors of Brent S. McKenzie
This figure shows the co-authorship network connecting the top 25 collaborators of Brent S. McKenzie. A scholar is included among the top collaborators of Brent S. McKenzie 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 Brent S. McKenzie. Brent S. McKenzie is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | Opportunities for Treg cell therapy for the treatment of human diseasebreakdown → | 70 |
| 2 | 68 | |
| 3 | 107 | |
| 4 | 52 | |
| 5 | 39 | |
| 6 | 182 | |
| 7 | 149 | |
| 8 | 128 | |
| 9 | 3 | |
| 10 | 131 | |
| 11 | 196 | |
| 12 | Development, cytokine profile and function of human interleukin 17–producing helper T cellsbreakdown → | 1628 |
| 13 | The Orphan Nuclear Receptor RORγt Directs the Differentiation Program of Proinflammatory IL-17+ T Helper Cellsbreakdown → | 4082 |
| 14 | 463 | |
| 15 | 63 | |
| 16 | Understanding the IL-23–IL-17 immune pathwaybreakdown → | 613 |
| 17 | 13 | |
| 18 | IL‐12 and IL‐23: master regulators of innate and adaptive immunitybreakdown → | 595 |
| 19 | 11 | |
| 20 | 13 |
About Brent S. McKenzie
Brent S. McKenzie is a scholar working on Immunology, Immunology and Allergy and Dermatology, having authored 45 papers that have together received 12.5k indexed citations. Recurring topics across this work include T-cell and B-cell Immunology (12 papers), Immune Cell Function and Interaction (11 papers) and IL-33, ST2, and ILC Pathways (9 papers). The work is most often cited by research in Immunology (9.6k citations), Dermatology (1.1k citations) and Pathology and Forensic Medicine (1.2k citations). Brent S. McKenzie has collaborated with scholars based in Australia, United Kingdom and United States. Frequent co-authors include J. Daniel, Robert A. Kastelein, Dan R. Littman, Ivaylo I. Ivanov, Carlos E. Tadokoro, Juan J. Lafaille, Liang Zhou, Alice Lepelley, Fiona Powrie and René de Waal Malefyt. Their work appears in journals such as Cell, Proceedings of the National Academy of Sciences and Journal of Clinical Investigation.
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.