Eric D. Watt

1.4k citations
21 papers · 1.2k · h-index 13

Impact in

Papers in

Eric D. Watt

20 papers receiving 1.2k citations

Peers

Eric D. Watt
Comparison fields: 5 of 93
  • Health, Toxicology and Mutagenesis 229
  • Spectroscopy 203
  • Molecular Biology 701
  • Small Animals 73
  • Biophysics 56
Replace Predrag Kukić with:
Predrag Kukić United Kingdom
Edith Monteagudo Italy
Élisabeth Darrouzet France
Joel M. Harp United States
Richard Clothier United Kingdom
Stephan Schwarzinger Germany
Jean‐Pierre Doucet France
Dean W. Goddette United States
Björn Windshügel Germany
Hualiang Jiang China
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Citations per field
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Predrag Kukić · 1×
Citations per year

Countries citing papers authored by Eric D. Watt

Since Specialization
Citations

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

Fields of papers citing papers by Eric D. Watt

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 21 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2006196
2 2016172
3 2008139
4 2007138
5 2016118
6 200883
7 200974
8 200865
9 201745
10 201839
11 201724
12 201321
13 201114
14 201512
15 20219
16 20229
17 20257
18 20245
19 20164
20 20242

About Eric D. Watt

Eric D. Watt is a scholar working on Molecular Biology, Health, Toxicology and Mutagenesis, Spectroscopy, Computational Theory and Mathematics and Cardiology and Cardiovascular Medicine, having authored 21 papers that have together received 1.2k indexed citations. Recurring topics across this work include Protein Structure and Dynamics (5 papers), Computational Drug Discovery Methods (4 papers), Advanced NMR Techniques and Applications (4 papers), Cardiac electrophysiology and arrhythmias (3 papers), DNA and Nucleic Acid Chemistry (3 papers), Effects and risks of endocrine disrupting chemicals (3 papers), Receptor Mechanisms and Signaling (2 papers) and Thyroid Disorders and Treatments (2 papers). The work is most often cited by research in Health, Toxicology and Mutagenesis (229 citations), Spectroscopy (203 citations), Molecular Biology (701 citations), Small Animals (73 citations) and Biophysics (56 citations). Eric D. Watt has collaborated with scholars based in United States, Denmark and United Kingdom. Frequent co-authors include J. Patrick Loria, Richard Judson, Hashim M. Al‐Hashimi, Qi Zhang, Xiaoyan Sun, Rebecca B. Berlow, Keith A. Houck, Hiroko Shimada, Evgenii L. Kovrigin and Nicolas Doucet. Their work appears in journals such as Regulatory Toxicology and Pharmacology, Chemical Research in Toxicology, Biophysical Journal, Toxicological Sciences and PLoS ONE.

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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