Nathaniel Barton

472 citations
10 papers · 369 · h-index 5

Impact in

  • Immunology top 10%
    • T-cell and B-cell Immunology
    • Immunotherapy and Immune Responses
    • Immune Cell Function and Interaction
    • Immune Response and Inflammation
    • IL-33, ST2, and ILC Pathways
    • Liver Diseases and Immunity

Papers in

    • Alzheimer's disease research and treatments 4
    • T-cell and B-cell Immunology 2
    • Immune Response and Inflammation 2

Nathaniel Barton

9 papers receiving 363 citations

Peers

Nathaniel Barton
Comparison fields: 5 of 33
  • Immunology 263
  • Hepatology 14
  • Infectious Diseases 26
  • Epidemiology 38
  • Virology 4
Replace Sara M. de la Harpe with:
Sara M. de la Harpe New Zealand
Xiangshu Wen United States
Morgan E. Parker United States
Yun Hee Jeong South Korea
Lenche Kostadinova United States
Angela Sambataro Italy
Moe Akahira-Azuma United States
Yasuyo Harada Japan
Chaitali P. Basole United States
Maiken L. Henriksen Denmark
Nathaniel Barton relative to Sara M. de la Harpe New Zealand Sara M. de la Harpe's profile →
Citations per field
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Sara M. de la Harpe · 1×
Citations per year

Countries citing papers authored by Nathaniel Barton

Since Specialization
Citations

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

Fields of papers citing papers by Nathaniel Barton

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Nathaniel Barton. 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 Nathaniel Barton. The network helps show where Nathaniel Barton may publish in the future.

Co-authors

The 25 scholars most cited alongside Nathaniel Barton, 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 Nathaniel Barton Line = papers co-authored together Nathaniel Barton links everyone, so they are left out of the graph.

All Works

10 of 10 papers shown
#Work
1 2011235
2 2013103
3 20249
4 20217
5 20235
6 20244
7 20233
8 20231
9 20251
10 20261

About Nathaniel Barton

Nathaniel Barton is a scholar working on Physiology, Immunology, Molecular Biology, Neurology and Epidemiology, having authored 10 papers that have together received 369 indexed citations. Recurring topics across this work include Alzheimer's disease research and treatments (4 papers), T-cell and B-cell Immunology (2 papers), Immune Response and Inflammation (2 papers), CRISPR and Genetic Engineering (2 papers), Herpesvirus Infections and Treatments (2 papers), Pluripotent Stem Cells Research (1 paper), Single-cell and spatial transcriptomics (1 paper) and Diabetes and associated disorders (1 paper). The work is most often cited by research in Immunology (263 citations), Hepatology (14 citations), Infectious Diseases (26 citations), Epidemiology (38 citations) and Virology (4 citations). Nathaniel Barton has collaborated with scholars based in United States, United Kingdom and Germany. Frequent co-authors include Manfred Brigl, Raju V. V. Tatituri, Gurdyal Singh Besra, Veemal Bhowruth, Fong‐Fu Hsu, Michael B. Brenner, Elizabeth A. Leadbetter, Nadia R. Cohen, Dale Ian Godfrey and Catarina F. Almeida. Their work appears in journals such as Alzheimer s & Dementia, Journal of Proteome Research, Human Genetics, Cells and The Journal of Experimental Medicine.

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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