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
-
- Bioinformatics and Genomic Networks 6
- CRISPR and Genetic Engineering 5
- DNA Repair Mechanisms 4
- Immunology 15
- T-cell and B-cell Immunology 10
- 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)Gil Atzmon (2 shared papers)Nir Barzilai (2 shared papers)Catherine Tang (6 shared papers)
- Journals
- Proceedings of the National Academy of Sciences (7 papers)PLoS Computational Biology (7 papers)BMC Evolutionary Biology (4 papers)Frontiers in Immunology (4 papers)Blood (3 papers)
- Partner nations
- United StatesUnited KingdomItaly
In The Last Decade
Thomas MacCarthy
48 papers receiving 905 citations
Peers
Comparison fields: 5 of 84
- Aging 48
- Immunology 273
- Virology 57
- Genetics 102
- Molecular Biology 487
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 | 52 | |
| 5 | 2012 | 44 | |
| 6 | 2007 | 41 | |
| 7 | 2007 | 38 | |
| 8 | 2017 | 38 | |
| 9 | 2008 | 33 | |
| 10 | 2009 | 32 | |
| 11 | 2016 | 28 | |
| 12 | 2018 | 27 | |
| 13 | 2016 | 23 | |
| 14 | 2013 | 23 | |
| 15 | 2019 | 22 | |
| 16 | 2020 | 22 | |
| 17 | 2014 | 19 | |
| 18 | 2005 | 17 | |
| 19 | 2013 | 15 | |
| 20 | 2014 | 14 |
About Thomas MacCarthy
Thomas MacCarthy is a scholar working on Molecular Biology, Immunology, Genetics, Genetics and Epidemiology, having authored 50 papers that have together received 914 indexed citations. Recurring topics across this work include T-cell and B-cell Immunology (10 papers), Monoclonal and Polyclonal Antibodies Research (6 papers), Immunodeficiency and Autoimmune Disorders (6 papers), Bioinformatics and Genomic Networks (6 papers), Chronic Lymphocytic Leukemia Research (6 papers), Evolution and Genetic Dynamics (5 papers), CRISPR and Genetic Engineering (5 papers) and DNA Repair Mechanisms (4 papers). The work is most often cited by research in Aging (48 citations), Immunology (273 citations), Virology (57 citations), Genetics (102 citations) and Molecular Biology (487 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, Gil Atzmon, Nir Barzilai, Catherine Tang, Andrew Pomiankowski and Robert M. Seymour. Their work appears in journals such as Proceedings of the National Academy of Sciences, PLoS Computational Biology, BMC Evolutionary Biology, Frontiers in Immunology 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.