Michael J. Reddish

693 citations
23 papers · 571 · h-index 13

Impact in

  • Pharmacology top 10%
    • Pharmacogenetics and Drug Metabolism
    • Immunotherapy and Immune Responses
    • Immune Cell Function and Interaction
    • T-cell and B-cell Immunology

Papers in

Michael J. Reddish

23 papers receiving 546 citations

Peers

Michael J. Reddish
Comparison fields: 5 of 89
  • Pharmacology 63
  • Immunology 140
  • Physical and Theoretical Chemistry 42
  • Molecular Biology 259
  • Radiology, Nuclear Medicine and Imaging 72
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Citations per field
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Citations per year

Countries citing papers authored by Michael J. Reddish

Since Specialization
Citations

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

Fields of papers citing papers by Michael J. Reddish

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 23 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Immune sera and monoclonal antibodies define two configurations for the sialyl Tn tumor antigen.
199587
2 199660
3 201053
4 201843
5 198439
6 201935
7 201430
8 201328
9 201926
10 199625
11 200920
12 201318
13 201515
14 201712
15 200912
16 201711
17
HLA-DR antigens and unique serologic reactions in juvenile-onset diabetes mellitus.
197811
18 202010
19 201010
20 20169

About Michael J. Reddish

Michael J. Reddish is a scholar working on Molecular Biology, Endocrinology, Diabetes and Metabolism, Immunology, Pharmacology and Biomedical Engineering, having authored 23 papers that have together received 571 indexed citations. Recurring topics across this work include Pharmacogenetics and Drug Metabolism (4 papers), Protein Structure and Dynamics (4 papers), Microfluidic and Capillary Electrophoresis Applications (4 papers), Hormonal and reproductive studies (3 papers), Hormonal Regulation and Hypertension (3 papers), Monoclonal and Polyclonal Antibodies Research (3 papers), Innovative Microfluidic and Catalytic Techniques Innovation (2 papers) and Hemoglobin structure and function (2 papers). The work is most often cited by research in Pharmacology (63 citations), Immunology (140 citations), Physical and Theoretical Chemistry (42 citations), Molecular Biology (259 citations) and Radiology, Nuclear Medicine and Imaging (72 citations). Michael J. Reddish has collaborated with scholars based in United States and Canada. Frequent co-authors include R. Brian Dyer, B. Michael Longenecker, F. Peter Guengerich, Babita Agrawal, Jeffrey T. Petty, Natalya N. Degtyareva, Bidisha Sengupta, Steven H. Itzkowitz, Sham S. Gandhi and Kenneth O. Lloyd. Their work appears in journals such as Biochemistry, The Journal of Immunology, Journal of Biological Chemistry, Lab on a Chip and The Journal of Physical Chemistry B.

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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