David Passmore

1.2k citations
24 papers · 724 · h-index 15

Impact in

Papers in

David Passmore

24 papers receiving 677 citations

Peers

David Passmore
Comparison fields: 5 of 63
  • Biotechnology 207
  • Radiology, Nuclear Medicine and Imaging 303
  • Immunology 280
  • Oncology 151
  • Molecular Biology 409
Replace Gordana Wozniak‐Knopp with:
Gordana Wozniak‐Knopp Austria
Kiran Khandke United States
Tiezheng Li United States
Brigitte Kaluza Germany
A.J. Cumber United Kingdom
Susan L. Bernhard United States
Jinbiao Zhan China
Maria‐Ana Ghetie United States
Jamie R. Rich Canada
Ragupathy Madiyalakan United States
David Passmore relative to Gordana Wozniak‐Knopp Austria Gordana Wozniak‐Knopp's profile →
Citations per field
00.5×1.5×2.4×
Gordana Wozniak‐Knopp · 1×
Citations per year

Countries citing papers authored by David Passmore

Since Specialization
Citations

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

Fields of papers citing papers by David Passmore

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside David Passmore, 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 David Passmore Line = papers co-authored together David Passmore 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 2006297
2 201549
3 200939
4 199535
5 201931
6 199329
7 199327
8 202026
9 201525
10 201825
11 199222
12 200921
13 201521
14 200421
15 199219
16 199210
17 19958
18 19946
19 20105
20 20122

About David Passmore

David Passmore is a scholar working on Radiology, Nuclear Medicine and Imaging, Immunology, Molecular Biology, Oncology and Organic Chemistry, having authored 24 papers that have together received 724 indexed citations. Recurring topics across this work include Monoclonal and Polyclonal Antibodies Research (15 papers), HER2/EGFR in Cancer Research (7 papers), Immunotherapy and Immune Responses (6 papers), Glycosylation and Glycoproteins Research (5 papers), T-cell and B-cell Immunology (5 papers), Computational Drug Discovery Methods (3 papers), Radiopharmaceutical Chemistry and Applications (3 papers) and Mass Spectrometry Techniques and Applications (2 papers). The work is most often cited by research in Biotechnology (207 citations), Radiology, Nuclear Medicine and Imaging (303 citations), Immunology (280 citations), Oncology (151 citations) and Molecular Biology (409 citations). David Passmore has collaborated with scholars based in United States, Germany and Sweden. Frequent co-authors include Pina M. Cardarelli, Bishwajit Nag, M. S. Srinivasan, Amelia Black, John R. Gasdaska, Lynn F. Dickey, Jason D. Sterling, Vangipuram S. Rangan, Brian R. Clark and Suresh D. Sharma. Their work appears in journals such as Cancer Research, Journal of Immunological Methods, The Journal of Immunology, Clinical Cancer Research and Cellular 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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