Eric S. Dawson

1.5k citations
42 papers · 1.1k · h-index 21

Impact in

Papers in

Eric S. Dawson

41 papers receiving 1.1k citations

Peers

Eric S. Dawson
Comparison fields: 5 of 118
  • Computational Theory and Mathematics 291
  • Cellular and Molecular Neuroscience 298
  • Infectious Diseases 184
  • Molecular Biology 645
  • Pharmacology 88
Replace Marcel Bermúdez with:
Marcel Bermúdez Germany
Vito Nacci Italy
Dina Manetti Italy
Yaxia Yuan United States
Mattia Sturlese Italy
Mauro Niso Italy
Paul L. Richardson United States
Simone Sciabola United States
David C. Pryde United Kingdom
David M. Shackleford Australia
Eric S. Dawson relative to Marcel Bermúdez Germany Marcel Bermúdez's profile →
Citations per field
00.5×4.2×
Marcel Bermúdez · 1×
Citations per year

Countries citing papers authored by Eric S. Dawson

Since Specialization
Citations

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

Fields of papers citing papers by Eric S. Dawson

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Eric S. Dawson. 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 Eric S. Dawson. The network helps show where Eric S. Dawson may publish in the future.

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 42 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2012159
2 2013100
3 201185
4 200980
5 200870
6 201063
7 200850
8 200645
9 201240
10 201038
11 201132
12 201430
13 201030
14 200627
15 201426
16 201124
17 199622
18 200822
19 200421
20 201021

About Eric S. Dawson

Eric S. Dawson is a scholar working on Molecular Biology, Cellular and Molecular Neuroscience, Oncology, Computational Theory and Mathematics and Cardiology and Cardiovascular Medicine, having authored 42 papers that have together received 1.1k indexed citations. Recurring topics across this work include Receptor Mechanisms and Signaling (18 papers), Neuroscience and Neuropharmacology Research (13 papers), Ion channel regulation and function (8 papers), Computational Drug Discovery Methods (5 papers), Neuropeptides and Animal Physiology (5 papers), Cardiac electrophysiology and arrhythmias (4 papers), Pharmacogenetics and Drug Metabolism (3 papers) and Drug Transport and Resistance Mechanisms (3 papers). The work is most often cited by research in Computational Theory and Mathematics (291 citations), Cellular and Molecular Neuroscience (298 citations), Infectious Diseases (184 citations), Molecular Biology (645 citations) and Pharmacology (88 citations). Eric S. Dawson has collaborated with scholars based in United States, Canada and Belgium. Frequent co-authors include Craig W. Lindsley, Jens Meiler, Shaun R. Stauffer, C. David Weaver, Valerie Grum‐Tokars, Peter Chase, Sakshi Tomar, Mark Turlington, Peter Hodder and Yahira M. Báez-Santos. Their work appears in journals such as Molecular Pharmacology, Bioorganic & Medicinal Chemistry Letters, Journal of Medicinal Chemistry, ACS Chemical Neuroscience and Bioconjugate Chemistry.

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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