Michael O’Dwyer

10.4k citations
161 papers · 4.4k · h-index 40

Impact in

  • Hematology top 0.5%
    • Chronic Myeloid Leukemia Treatments
    • Acute Myeloid Leukemia Research
    • Multiple Myeloma Research and Treatments
  • Genetics top 1%
    • Chronic Lymphocytic Leukemia Research

Papers in

    • Multiple Myeloma Research and Treatments 43
    • Chronic Myeloid Leukemia Treatments 34
    • Acute Myeloid Leukemia Research 21
    • Glycosylation and Glycoproteins Research 18

Michael O’Dwyer

155 papers receiving 4.3k citations

Peers

Michael O’Dwyer
Comparison fields: 5 of 143
  • Hematology 1.4k
  • Genetics 749
  • Immunology 911
  • Oncology 898
  • Molecular Biology 1.9k
Replace Taira Maekawa with:
Taira Maekawa Japan
Junji Kato Japan
Matthias Mayerhofer Austria
Masayoshi Kobune Japan
Georges Uzan France
Tatsuo Abe Japan
Jianxiang Wang China
Xi Zhang China
Weina Chen United States
Surapol Issaragrisil Thailand
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Citations per field
00.5×
Taira Maekawa · 1×
Citations per year

Countries citing papers authored by Michael O’Dwyer

Since Specialization
Citations

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

Fields of papers citing papers by Michael O’Dwyer

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Michael O’Dwyer. 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 O’Dwyer. The network helps show where Michael O’Dwyer may publish in the future.

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 161 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2010221
2 2020210
3 2015177
4 2016165
5 2013129
6 2016108
7 2002104
8 2014103
9 201995
10 202094
11 200990
12 201585
13 200982
14 201580
15 200280
16 200379
17 201978
18 200275
19 200274
20 200373

About Michael O’Dwyer

Michael O’Dwyer is a scholar working on Hematology, Molecular Biology, Oncology, Genetics and Immunology, having authored 161 papers that have together received 4.4k indexed citations. Recurring topics across this work include Multiple Myeloma Research and Treatments (43 papers), Chronic Lymphocytic Leukemia Research (39 papers), Chronic Myeloid Leukemia Treatments (34 papers), Immune Cell Function and Interaction (26 papers), Acute Myeloid Leukemia Research (21 papers), Glycosylation and Glycoproteins Research (18 papers), Eosinophilic Disorders and Syndromes (16 papers) and CAR-T cell therapy research (14 papers). The work is most often cited by research in Hematology (1.4k citations), Genetics (749 citations), Immunology (911 citations), Oncology (898 citations) and Molecular Biology (1.9k citations). Michael O’Dwyer has collaborated with scholars based in Ireland, United States and United Kingdom. Frequent co-authors include Brian Druker, Alessandro Natoni, Michael J. Mauro, Ronan Swords, Mark E. Gurney, Afshin Samali, Lokesh Joshi, Paul La Rosée, Francis J. Giles and Matthew S. Macauley. Their work appears in journals such as Blood, Journal of Clinical Oncology, Leukemia, Cancers and Blood Advances.

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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