Ruby Quartey‐Papafio

839 citations
24 papers · 735 · h-index 13

Impact in

  • Immunology top 5%
    • T-cell and B-cell Immunology
    • Immune Cell Function and Interaction
    • Immunodeficiency and Autoimmune Disorders
  • Genetics top 10%
    • Diabetes and associated disorders
    • Chronic Lymphocytic Leukemia Research

Papers in

Ruby Quartey‐Papafio

23 papers receiving 677 citations

Peers

Ruby Quartey‐Papafio
Comparison fields: 5 of 57
  • Immunology 458
  • Genetics 124
  • Virology 42
  • Radiology, Nuclear Medicine and Imaging 183
  • Genetics 186
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Citations per year

Countries citing papers authored by Ruby Quartey‐Papafio

Since Specialization
Citations

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

Fields of papers citing papers by Ruby Quartey‐Papafio

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Ruby Quartey‐Papafio. 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 Ruby Quartey‐Papafio. The network helps show where Ruby Quartey‐Papafio may publish in the future.

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 24 papers — load more, or switch the sort, to bring in the rest.

#Work
1 1988144
2 1980112
3 199072
4 199571
5 198064
6 199338
7 199032
8 199331
9 199529
10 199024
11
Recognition of thyroglobulin autoantigenic epitopes by murine T and B cells.
198719
12 198416
13 198314
14 200611
15 201410
16 201510
17 19909
18 19967
19 20116
20 20125

About Ruby Quartey‐Papafio

Ruby Quartey‐Papafio is a scholar working on Immunology, Radiology, Nuclear Medicine and Imaging, Molecular Biology, Genetics and Virology, having authored 24 papers that have together received 735 indexed citations. Recurring topics across this work include T-cell and B-cell Immunology (12 papers), Monoclonal and Polyclonal Antibodies Research (8 papers), Immune Cell Function and Interaction (6 papers), Diabetes and associated disorders (5 papers), HIV Research and Treatment (4 papers), Lymphoma Diagnosis and Treatment (3 papers), Glycosylation and Glycoproteins Research (2 papers) and Immunotherapy and Immune Responses (2 papers). The work is most often cited by research in Immunology (458 citations), Genetics (124 citations), Virology (42 citations), Radiology, Nuclear Medicine and Imaging (183 citations) and Genetics (186 citations). Ruby Quartey‐Papafio has collaborated with scholars based in United Kingdom, France and United States. Frequent co-authors include Anthony A. Nash, H. J. Field, Peter M. Lydyard, Pierre Youinou, Lorna Mackenzie, Barbara M. Bröker, P. Wildy, Jean Jouquan, M Blaschek and Anne Cooke. Their work appears in journals such as Scandinavian Journal of Immunology, Retrovirology, European Journal of Immunology, Journal of General Virology and Journal of Autoimmunity.

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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