G J Freeman

3.0k citations
25 papers · 2.6k · h-index 21

Impact in

  • Immunology top 1%
    • T-cell and B-cell Immunology
    • Immune Cell Function and Interaction
    • Immunotherapy and Immune Responses
    • Immune Response and Inflammation

Papers in

    • Immunotherapy and Immune Responses 14
    • T-cell and B-cell Immunology 14
    • Immune Cell Function and Interaction 12
    • Cancer Immunotherapy and Biomarkers 5

G J Freeman

25 papers receiving 2.5k citations

Peers

G J Freeman
Comparison fields: 5 of 87
  • Immunology 1.8k
  • Immunology and Allergy 164
  • Oncology 457
  • Hematology 139
  • Transplantation 29
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Citations per field
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Citations per year

Countries citing papers authored by G J Freeman

Since Specialization
Citations

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

Fields of papers citing papers by G J Freeman

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by G J Freeman. 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 G J Freeman. The network helps show where G J Freeman may publish in the future.

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 25 papers — load more, or switch the sort, to bring in the rest.

#Work
1 1993484
2 1993275
3 1994254
4 1996224
5 1995150
6 1994137
7 1995123
8 1992118
9 1992104
10 199497
11 199678
12 199276
13 199474
14 199770
15 199761
16 199756
17 199451
18
mAb 104, a new monoclonal antibody, recognizes the B7 antigen that is expressed on activated B cells and HTLV-1-transformed T cells.
199039
19 199437
20 199627

About G J Freeman

G J Freeman is a scholar working on Immunology, Oncology, Molecular Biology, Radiology, Nuclear Medicine and Imaging and Genetics, having authored 25 papers that have together received 2.6k indexed citations. Recurring topics across this work include Immunotherapy and Immune Responses (14 papers), T-cell and B-cell Immunology (14 papers), Immune Cell Function and Interaction (12 papers), Cancer Immunotherapy and Biomarkers (5 papers), Monoclonal and Polyclonal Antibodies Research (3 papers), Glycosylation and Glycoproteins Research (2 papers), Diabetes and associated disorders (2 papers) and Cell Adhesion Molecules Research (2 papers). The work is most often cited by research in Immunology (1.8k citations), Immunology and Allergy (164 citations), Oncology (457 citations), Hematology (139 citations) and Transplantation (29 citations). G J Freeman has collaborated with scholars based in United States and Canada. Frequent co-authors include G S Gray, Lee M. Nadler, John G. Gribben, Claude Gimmi, L M Nadler, Vassiliki A. Boussiotis, Hiroshi Uchiyama, Mitsuyoshi Urashima, KC Anderson and D Chauhan. Their work appears in journals such as The Journal of Immunology, Proceedings of the National Academy of Sciences, The Journal of Experimental Medicine, Blood and Journal of Clinical Investigation.

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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