Dat P. Mao
Impact in
- Immunology top 2%
- Immune Response and Inflammation
- interferon and immune responses
- IL-33, ST2, and ILC Pathways
- Endocrinology top 2%
- Vibrio bacteria research studies
Papers in
-
- Inflammasome and immune disorders 7
- Cell death mechanisms and regulation 1
-
- Immune Response and Inflammation 4
- interferon and immune responses 3
- IL-33, ST2, and ILC Pathways 1
- Phagocytosis and Immune Regulation 1
- Co-authors
- Edward A. Miao (8 shared papers)Alan Aderem (8 shared papers)Sarah Warren (5 shared papers)Irina A. Leaf (5 shared papers)Monica Dors (2 shared papers)Anasuya Sarkar (2 shared papers)Mark D. Wewers (2 shared papers)Piper M. Treuting (1 shared paper)
- Journals
- The Journal of Immunology (3 papers)Proceedings of the National Academy of Sciences (2 papers)Nature Immunology (1 paper)Cell Host & Microbe (1 paper)European Journal of Immunology (1 paper)
- Partner nations
- United StatesIreland
In The Last Decade
Dat P. Mao
8 papers receiving 2.3k citations
Hit Papers
Peers
Comparison fields: 5 of 88
- Immunology 1.2k
- Endocrinology 230
- Molecular Biology 1.9k
- Nephrology 180
- Molecular Medicine 67
Countries citing papers authored by Dat P. Mao
This map shows the geographic impact of Dat P. Mao'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 Dat P. Mao with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Dat P. Mao more than expected).
Fields of papers citing papers by Dat P. Mao
This network shows the impact of papers produced by Dat P. Mao. 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 Dat P. Mao. The network helps show where Dat P. Mao may publish in the future.
Co-authors
The 21 scholars most cited alongside Dat P. Mao, 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 | Caspase-1-induced pyroptosis is an innate immune effector mechanism against intracellular bacteria Hit paper breakdown → | 2010 | 1064 |
| 2 | Innate immune detection of the type III secretion apparatus through the NLRC4 inflammasome Hit paper breakdown → | 2010 | 629 |
| 3 | 2008 | 240 | |
| 4 | 2008 | 153 | |
| 5 | 2010 | 117 | |
| 6 | 2015 | 101 | |
| 7 | 2011 | 31 | |
| 8 | 2011 | 21 |
About Dat P. Mao
Dat P. Mao is a scholar working on Molecular Biology, Immunology, Cell Biology, Endocrinology and Infectious Diseases, having authored 8 papers that have together received 2.4k indexed citations. Recurring topics across this work include Inflammasome and immune disorders (7 papers), Immune Response and Inflammation (4 papers), interferon and immune responses (3 papers), Endoplasmic Reticulum Stress and Disease (3 papers), Cell death mechanisms and regulation (1 paper), Vibrio bacteria research studies (1 paper), IL-33, ST2, and ILC Pathways (1 paper) and Phagocytosis and Immune Regulation (1 paper). The work is most often cited by research in Immunology (1.2k citations), Endocrinology (230 citations), Molecular Biology (1.9k citations), Nephrology (180 citations) and Molecular Medicine (67 citations). Dat P. Mao has collaborated with scholars based in United States and Ireland. Frequent co-authors include Edward A. Miao, Alan Aderem, Sarah Warren, Irina A. Leaf, Monica Dors, Anasuya Sarkar, Mark D. Wewers, Piper M. Treuting, Natalya Yudkovsky and Richard Bonneau. Their work appears in journals such as The Journal of Immunology, Proceedings of the National Academy of Sciences, Nature Immunology, Cell Host & Microbe and European Journal of Immunology.
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.