David O'Hanlon

1.4k citations
15 papers · 1.2k · h-index 14

Impact in

Papers in

    • S100 Proteins and Annexins 13
    • Machine Learning in Bioinformatics 3
    • Connexins and lens biology 3
    • Signaling Pathways in Disease 2
    • Immune Response and Inflammation 4

David O'Hanlon

15 papers receiving 1.1k citations

Peers

David O'Hanlon
Comparison fields: 5 of 75
  • Pathology and Forensic Medicine 298
  • Molecular Biology 720
  • Immunology 204
  • Neurology 132
  • Cancer Research 126
Replace Michael J. Chao with:
Michael J. Chao United Kingdom
Frank Brand United States
Manuel Zeitelhofer Sweden
Marie‐Lune Simard Germany
Ryan T. Mott United States
Robert D. Mair United States
Irena Dujmović Serbia
Thomas W. Smith United States
Giulia Mallucci Italy
David O'Hanlon relative to Michael J. Chao United Kingdom Michael J. Chao's profile →
Citations per field
00.5×3.4×
Michael J. Chao · 1×
Citations per year

Countries citing papers authored by David O'Hanlon

Since Specialization
Citations

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

Fields of papers citing papers by David O'Hanlon

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

15 of 15 papers shown
#Work
1 2001302
2 1988210
3 2000107
4 199280
5 199072
6 199867
7 199750
8 198750
9 199348
10 199947
11 199040
12 199634
13 200425
14 200324
15 20233

About David O'Hanlon

David O'Hanlon is a scholar working on Molecular Biology, Immunology, Cardiology and Cardiovascular Medicine, Neurology and Cancer Research, having authored 15 papers that have together received 1.2k indexed citations. Recurring topics across this work include S100 Proteins and Annexins (13 papers), Immune Response and Inflammation (4 papers), Machine Learning in Bioinformatics (3 papers), Connexins and lens biology (3 papers), Cardiac Fibrosis and Remodeling (3 papers), Traumatic Brain Injury and Neurovascular Disturbances (2 papers), Signaling Pathways in Disease (2 papers) and Protease and Inhibitor Mechanisms (2 papers). The work is most often cited by research in Pathology and Forensic Medicine (298 citations), Molecular Biology (720 citations), Immunology (204 citations), Neurology (132 citations) and Cancer Research (126 citations). David O'Hanlon has collaborated with scholars based in Canada, United States and Argentina. Frequent co-authors include Alexander Marks, Robert Dunn, R. Allore, Karen M. Neilson, John Roder, Thomas G. Parker, David R. Cox, James N. Tsoporis, H F Willard and Richard H. Price. Their work appears in journals such as Experimental Cell Research, Journal of Biological Chemistry, Journal of Neuroscience, Journal of Clinical Investigation and Science.

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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