David Pearson

2.8k citations
50 papers · 2.5k · h-index 24

Impact in

Papers in

    • RNA and protein synthesis mechanisms 6
    • RNA Research and Splicing 5
    • Signaling Pathways in Disease 5
    • Glycosylation and Glycoproteins Research 4
    • Protease and Inhibitor Mechanisms 10

David Pearson

49 papers receiving 2.4k citations

Peers

David Pearson
Comparison fields: 5 of 123
  • Immunology and Allergy 455
  • Pharmacology 389
  • Cancer Research 305
  • Cell Biology 308
  • Hematology 185
Replace Pellegrino Rossi with:
Pellegrino Rossi Italy
Daniel H. Cohn United States
Kathleen A. Sullivan United States
Charlene J. Williams United States
Walter E. Horton United States
Michael P. Sarras United States
Dominic Cosgrove United States
Orest W. Blaschuk Canada
Hirofumi Ohashi Japan
Ted S. Acott United States
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Citations per field
00.5×2×3.1×
Pellegrino Rossi · 1×
Citations per year

Countries citing papers authored by David Pearson

Since Specialization
Citations

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

Fields of papers citing papers by David Pearson

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 50 papers — load more, or switch the sort, to bring in the rest.

#Work
1 1988428
2 1980339
3 1985191
4 1988135
5 2000126
6 1984112
7 2004105
8 2004100
9 199974
10 198468
11 198268
12 198761
13 198559
14 199151
15 198846
16 199439
17 199238
18 199036
19 201136
20 201930

About David Pearson

David Pearson is a scholar working on Molecular Biology, Cancer Research, Surgery, Cell Biology and Cellular and Molecular Neuroscience, having authored 50 papers that have together received 2.5k indexed citations. Recurring topics across this work include Protease and Inhibitor Mechanisms (10 papers), RNA and protein synthesis mechanisms (6 papers), RNA Research and Splicing (5 papers), Signaling Pathways in Disease (5 papers), Glycosylation and Glycoproteins Research (4 papers), Cardiovascular, Neuropeptides, and Oxidative Stress Research (4 papers), Hormonal Regulation and Hypertension (4 papers) and Cell Adhesion Molecules Research (4 papers). The work is most often cited by research in Immunology and Allergy (455 citations), Pharmacology (389 citations), Cancer Research (305 citations), Cell Biology (308 citations) and Hematology (185 citations). David Pearson has collaborated with scholars based in United States, Switzerland and United Kingdom. Frequent co-authors include Howard A. Bern, Shigeki Shibahara, Yoshikuni Nagamine, Jan Hofsteenge, Ruth Chiquet‐Ehrismann, Scott I. Simon, Michael S. Altus, Brian R. Clark, Irving I. Geschwind and John E. Shively. Their work appears in journals such as Nucleic Acids Research, Journal of Biological Chemistry, Molecular and Cellular Biology, The EMBO Journal and Molecular Imaging.

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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