Thomas MacCarthy
Impact in
- Aging top 5%
- Immunology top 10%
- T-cell and B-cell Immunology
- Immune Cell Function and Interaction
- Immunodeficiency and Autoimmune Disorders
Papers in ⓘ
- Aging 2
- Immunology 17
- T-cell and B-cell Immunology 12
- Immunodeficiency and Autoimmune Disorders 6
- Co-authors
- Aviv Bergman (14 shared papers)Matthew D. Scharff (13 shared papers)Sergio Roa (5 shared papers)Jeffrey Chen (1 shared paper)Kenny Ye (2 shared papers)Nir Barzilai (2 shared papers)Gil Atzmon (2 shared papers)Catherine Tang (6 shared papers)
- Journals
- PLoS Computational Biology (7 papers)Proceedings of the National Academy of Sciences (7 papers)Frontiers in Immunology (4 papers)BMC Evolutionary Biology (4 papers)Blood (3 papers)
- Partner nations
- United StatesUnited KingdomItaly
In The Last Decade
Thomas MacCarthy
49 papers receiving 891 citations
Peers
Comparison fields: 5 of 86
- Aging 48
- Immunology 286
- Virology 59
- Genetics 106
- Molecular Biology 505
Countries citing papers authored by Thomas MacCarthy
This map shows the geographic impact of Thomas MacCarthy'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 Thomas MacCarthy with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Thomas MacCarthy more than expected).
Fields of papers citing papers by Thomas MacCarthy
This network shows the impact of papers produced by Thomas MacCarthy. 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 Thomas MacCarthy. The network helps show where Thomas MacCarthy may publish in the future.
Co-authors
The 25 scholars most cited alongside Thomas MacCarthy, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 50 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2008 | 94 | |
| 2 | 2007 | 88 | |
| 3 | 2012 | 59 | |
| 4 | 2015 | 51 | |
| 5 | 2012 | 44 | |
| 6 | 2007 | 41 | |
| 7 | 2017 | 39 | |
| 8 | 2007 | 38 | |
| 9 | 2008 | 33 | |
| 10 | 2009 | 32 | |
| 11 | 2016 | 28 | |
| 12 | 2018 | 27 | |
| 13 | 2016 | 23 | |
| 14 | 2013 | 23 | |
| 15 | 2020 | 21 | |
| 16 | 2019 | 21 | |
| 17 | 2014 | 19 | |
| 18 | 2005 | 17 | |
| 19 | 2013 | 15 | |
| 20 | 2014 | 14 |
About Thomas MacCarthy
Thomas MacCarthy is a scholar working on Aging, Immunology, Virology, Genetics and Molecular Biology, having authored 50 papers that have together received 900 indexed citations. Recurring topics across this work include T-cell and B-cell Immunology (12 papers), Monoclonal and Polyclonal Antibodies Research (7 papers), Chronic Lymphocytic Leukemia Research (6 papers), Evolution and Genetic Dynamics (6 papers), Immunodeficiency and Autoimmune Disorders (6 papers), Bioinformatics and Genomic Networks (6 papers), CRISPR and Genetic Engineering (5 papers) and Genomics and Chromatin Dynamics (5 papers). The work is most often cited by research in Aging (48 citations), Immunology (286 citations), Virology (59 citations), Genetics (106 citations) and Molecular Biology (505 citations). Thomas MacCarthy has collaborated with scholars based in United States, United Kingdom and Italy. Frequent co-authors include Aviv Bergman, Matthew D. Scharff, Sergio Roa, Jeffrey Chen, Kenny Ye, Nir Barzilai, Gil Atzmon, Catherine Tang, Andrew Pomiankowski and Robert M. Seymour. Their work appears in journals such as PLoS Computational Biology, Proceedings of the National Academy of Sciences, Frontiers in Immunology, BMC Evolutionary Biology and Blood.
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.