Michael A. Derby

1.8k citations
31 papers · 1.5k · h-index 19

Impact in

  • Virology top 2%
    • HIV Research and Treatment
  • Immunology top 5%
    • Immune Cell Function and Interaction
    • Immunotherapy and Immune Responses
    • T-cell and B-cell Immunology

Papers in

    • Glycosylation and Glycoproteins Research 3
    • Influenza Virus Research Studies 4
    • Herpesvirus Infections and Treatments 3

Michael A. Derby

30 papers receiving 1.5k citations

Peers

Michael A. Derby
Comparison fields: 5 of 92
  • Virology 233
  • Immunology 735
  • Cell Biology 206
  • Immunology and Allergy 67
  • Epidemiology 363
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Citations per field
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Citations per year

Countries citing papers authored by Michael A. Derby

Since Specialization
Citations

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

Fields of papers citing papers by Michael A. Derby

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Michael A. Derby. 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 Michael A. Derby. The network helps show where Michael A. Derby may publish in the future.

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 31 papers — load more, or switch the sort, to bring in the rest.

#Work
1 1998231
2 2001173
3 1978163
4 1978120
5 199886
6 199980
7 201677
8
Interaction of murine MHC class I molecules with tapasin and TAP enhances peptide loading and involves the heavy chain alpha3 domain.
199975
9 199969
10 201762
11 200155
12 200155
13 200752
14 201644
15 201533
16 200730
17 201723
18 200123
19 198123
20 201712

About Michael A. Derby

Michael A. Derby is a scholar working on Molecular Biology, Epidemiology, Immunology, Cardiology and Cardiovascular Medicine and Virology, having authored 31 papers that have together received 1.5k indexed citations. Recurring topics across this work include Immune Cell Function and Interaction (7 papers), Immunotherapy and Immune Responses (5 papers), T-cell and B-cell Immunology (4 papers), Influenza Virus Research Studies (4 papers), HIV Research and Treatment (4 papers), Cardiac electrophysiology and arrhythmias (3 papers), Glycosylation and Glycoproteins Research (3 papers) and Herpesvirus Infections and Treatments (3 papers). The work is most often cited by research in Virology (233 citations), Immunology (735 citations), Cell Biology (206 citations), Immunology and Allergy (67 citations) and Epidemiology (363 citations). Michael A. Derby has collaborated with scholars based in United States, France and Canada. Frequent co-authors include Jay A. Berzofsky, Martha A. Alexander‐Miller, John E. Pintar, Igor M. Belyakov, Jeffrey D. Ahlers, Bernard Moss, Brian L. Kelsall, Patricia L. Earl, Warren Strober and David B. Williams. Their work appears in journals such as Antimicrobial Agents and Chemotherapy, The Journal of Immunology, Clinical Pharmacology & Therapeutics, Journal of Cardiovascular Pharmacology and Developmental Brain Research.

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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