John Apgar

3.9k citations
38 papers · 3.2k · h-index 23

Impact in

  • Immunology top 1%
    • Galectins and Cancer Biology
    • Immune Cell Function and Interaction
    • T-cell and B-cell Immunology
  • Genetics top 2%
    • Chronic Lymphocytic Leukemia Research

Papers in

    • Immune Cell Function and Interaction 9
    • T-cell and B-cell Immunology 8
    • Mast cells and histamine 5
    • Galectins and Cancer Biology 5
    • Immunotherapy and Immune Responses 5
    • Glycosylation and Glycoproteins Research 6

John Apgar

38 papers receiving 3.2k citations

Peers

John Apgar
Comparison fields: 5 of 116
  • Immunology 1.9k
  • Genetics 352
  • Immunology and Allergy 189
  • Molecular Biology 1.5k
  • Hematology 164
Replace Raul M. Torres with:
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John Apgar relative to Raul M. Torres United States Raul M. Torres's profile →
Citations per field
00.5×1.5×1.8×
Raul M. Torres · 1×
Citations per year

Countries citing papers authored by John Apgar

Since Specialization
Citations

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

Fields of papers citing papers by John Apgar

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 38 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2000423
2 2004395
3 2003304
4 2003302
5 2017227
6 1992195
7 2004186
8 2004147
9 1980115
10 1999114
11 2007112
12 1999110
13 199156
14 199250
15 199542
16 200040
17 200039
18 199038
19 198536
20 199136

About John Apgar

John Apgar is a scholar working on Immunology, Molecular Biology, Radiology, Nuclear Medicine and Imaging, Oncology and Cell Biology, having authored 38 papers that have together received 3.2k indexed citations. Recurring topics across this work include Immune Cell Function and Interaction (9 papers), T-cell and B-cell Immunology (8 papers), Monoclonal and Polyclonal Antibodies Research (7 papers), Glycosylation and Glycoproteins Research (6 papers), Mast cells and histamine (5 papers), Galectins and Cancer Biology (5 papers), Immunotherapy and Immune Responses (5 papers) and Chronic Lymphocytic Leukemia Research (4 papers). The work is most often cited by research in Immunology (1.9k citations), Genetics (352 citations), Immunology and Allergy (189 citations), Molecular Biology (1.5k citations) and Hematology (164 citations). John Apgar has collaborated with scholars based in United States, Japan and Switzerland. Frequent co-authors include Fu‐Tong Liu, Daniel K. Hsu, Lan Yu, Ichiro Kuwabara, Hideki Sano, Bhavya Bhavna Sharma, Shozo Izui, Luciano G. Frigeri, Mitsuomi Hirashima and Tohru Yamanaka. Their work appears in journals such as The Journal of Immunology, The Journal of Cell Biology, Molecular Biology of the Cell, Blood 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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