Todd N. Eagar

68 papers receiving 4.3k citations

Todd N. Eagar's Hit Papers

T cell subsets and their signature cytokines in autoimmune and inflammatory diseases 2014 · 929 citations
9290+4+8Years since publication250500750

Peers

Todd N. Eagar
Comparison fields: 5 of 113
  • Immunology 1.1k
  • Pathology and Forensic Medicine 818
  • Infectious Diseases 774
  • Oncology 482
  • Molecular Medicine 106
Replace Amit Awasthi with:
Amit Awasthi India
Hisakata Yamada Japan
Joanne E. Konkel United Kingdom
Harumichi Ishigame Japan
Aya Nambu Japan
Caroline E. Sutton Ireland
Xiang‐Ping Yang China
Sascha Rutz Germany
Gustavo Martínez United States
Thomas G. Forsthuber United States
Todd N. Eagar relative to Amit Awasthi India Amit Awasthi's profile →
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Countries citing papers authored by Todd N. Eagar

Since Specialization
Citations

This map shows the geographic impact of Todd N. Eagar'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 Todd N. Eagar with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Todd N. Eagar more than expected).

Fields of papers citing papers by Todd N. Eagar

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Todd N. Eagar. 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 Todd N. Eagar. The network helps show where Todd N. Eagar may publish in the future.

Co-authors

The 25 scholars most cited alongside Todd N. Eagar, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Todd N. Eagar Line = papers co-authored together Todd N. Eagar links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 71 papers — load more, or switch the sort, to bring in the rest.

#Work
1
T cell subsets and their signature cytokines in autoimmune and inflammatory diseases
Hit paper breakdown →
2014929
2 2009636
3 2006281
4 2020233
5 2020184
6 2000182
7 2020169
8 1998152
9 2004135
10 2020125
11 2017117
12 2010101
13 200198
14 200294
15 200586
16 200969
17 201169
18 199861
19 200050
20 200248

About Todd N. Eagar

Todd N. Eagar is a scholar working on Pathology and Forensic Medicine, Immunology, Transplantation, Infectious Diseases and Physiology, having authored 71 papers that have together received 4.4k indexed citations. Recurring topics across this work include Multiple Sclerosis Research Studies (29 papers), T-cell and B-cell Immunology (15 papers), SARS-CoV-2 and COVID-19 Research (7 papers), Renal Transplantation Outcomes and Treatments (6 papers), Alzheimer's disease research and treatments (4 papers), COVID-19 Clinical Research Studies (3 papers), Prion Diseases and Protein Misfolding (3 papers) and Transplantation: Methods and Outcomes (2 papers). The work is most often cited by research in Immunology (1.1k citations), Pathology and Forensic Medicine (818 citations), Infectious Diseases (774 citations), Oncology (482 citations) and Molecular Medicine (106 citations). Todd N. Eagar has collaborated with scholars based in United States, Germany and Israel. Frequent co-authors include Thomas G. Forsthuber, Itay Raphael, Saisha Abhay Nalawade, Jeffrey A. Bluestone, Stephen D. Miller, Qizhi Tang, Brian T. Fife, Miyuki Azuma, Carol L. Vanderlugt and Jenny Qun Wu. Their work appears in journals such as Clinical Immunology, Journal of Neuroimmunology, Clinical Transplantation, PLoS ONE 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.

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