Michael Feolo
Impact in
-
- T-cell and B-cell Immunology
- Immune Cell Function and Interaction
- Genetics top 10%
- Genetic Associations and Epidemiology
- Genomics and Rare Diseases
- Diabetes and associated disorders
Papers in
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- Glycosylation and Glycoproteins Research 2
- Immunology 11
- T-cell and B-cell Immunology 10
- Immune Cell Function and Interaction 4
- Immunotherapy and Immune Responses 3
- Co-authors
- Yumi Jin (3 shared papers)Masato Kimura (2 shared papers)Nataliya Sharopova (2 shared papers)Zhen Y Wang (1 shared paper)Moira Lee (1 shared paper)Н. В. Попова (1 shared paper)Lora Ziyabari (1 shared paper)K. A. Tryka (1 shared paper)
- Journals
- PLoS ONE (3 papers)Human Immunology (2 papers)Nucleic Acids Research (2 papers)G3 Genes Genomes Genetics (1 paper)The Journal of Immunology (1 paper)
- Partner nations
- United StatesAustriaFrance
In The Last Decade
Michael Feolo
22 papers receiving 711 citations
Peers
Comparison fields: 5 of 94
- Immunology 195
- Genetics 243
- Cancer Research 103
- Molecular Biology 328
- Gastroenterology 19
Countries citing papers authored by Michael Feolo
This map shows the geographic impact of Michael Feolo'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 Michael Feolo with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Michael Feolo more than expected).
Fields of papers citing papers by Michael Feolo
This network shows the impact of papers produced by Michael Feolo. 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 Michael Feolo. The network helps show where Michael Feolo may publish in the future.
Co-authors
The 25 scholars most cited alongside Michael Feolo, 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 22 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2013 | 321 | |
| 2 | 2014 | 122 | |
| 3 | 2011 | 40 | |
| 4 | 2019 | 33 | |
| 5 | 2007 | 29 | |
| 6 | 1995 | 28 | |
| 7 | 2004 | 26 | |
| 8 | 1994 | 23 | |
| 9 | 2005 | 21 | |
| 10 | 2009 | 21 | |
| 11 | 2001 | 18 | |
| 12 | 2017 | 15 | |
| 13 | 2006 | 9 | |
| 14 | 2007 | 7 | |
| 15 | 2022 | 4 | |
| 16 | 2022 | 3 | |
| 17 | 2003 | 2 | |
| 18 | 2004 | 2 | |
| 19 | 2007 | 2 | |
| 20 | 2009 | 1 |
About Michael Feolo
Michael Feolo is a scholar working on Molecular Biology, Immunology, Genetics, Pathology and Forensic Medicine and Epidemiology, having authored 22 papers that have together received 729 indexed citations. Recurring topics across this work include T-cell and B-cell Immunology (10 papers), Genetic Associations and Epidemiology (7 papers), Immune Cell Function and Interaction (4 papers), Genetic and phenotypic traits in livestock (3 papers), Genetic Mapping and Diversity in Plants and Animals (3 papers), Immunotherapy and Immune Responses (3 papers), Cancer-related molecular mechanisms research (2 papers) and Glycosylation and Glycoproteins Research (2 papers). The work is most often cited by research in Immunology (195 citations), Genetics (243 citations), Cancer Research (103 citations), Molecular Biology (328 citations) and Gastroenterology (19 citations). Michael Feolo has collaborated with scholars based in United States, Austria and France. Frequent co-authors include Yumi Jin, Masato Kimura, Nataliya Sharopova, Zhen Y Wang, Moira Lee, Н. В. Попова, Lora Ziyabari, K. A. Tryka, Luning Hao and Anne Sturcke. Their work appears in journals such as PLoS ONE, Human Immunology, Nucleic Acids Research, G3 Genes Genomes Genetics and The 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.