Eric D. Watt

1.4k citations
22 papers · 1.1k · h-index 13

Impact in

Papers in

Eric D. Watt

21 papers receiving 1.1k citations

Peers

Eric D. Watt
Comparison fields: 5 of 91
  • Health, Toxicology and Mutagenesis 224
  • Spectroscopy 197
  • Molecular Biology 700
  • Biophysics 56
  • Small Animals 71
Replace Alessandro Pandini with:
Alessandro Pandini United Kingdom
Predrag Kukić United Kingdom
Edith Monteagudo Italy
Richard Clothier United Kingdom
Stephan Schwarzinger Germany
Joel M. Harp United States
Kiyoshi Sasaki Japan
Dean W. Goddette United States
Jean‐Pierre Doucet France
Benjamin D. Madej United States
Eric D. Watt relative to Alessandro Pandini United Kingdom Alessandro Pandini's profile →
Citations per field
00.5×10×15×17.8×
Alessandro Pandini · 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 22 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2006189
2 2016157
3 2007137
4 2008130
5 2016113
6 200882
7 200972
8 200862
9 201744
10 201837
11 201722
12 201321
13 201114
14 201512
15 20219
16 20227
17 20245
18 20255
19 20164
20 20241

About Eric D. Watt

Eric D. Watt is a scholar working on Molecular Biology, Computational Theory and Mathematics, Health, Toxicology and Mutagenesis, Spectroscopy and Cardiology and Cardiovascular Medicine, having authored 22 papers that have together received 1.1k indexed citations. Recurring topics across this work include Computational Drug Discovery Methods (6 papers), Protein Structure and Dynamics (5 papers), Advanced NMR Techniques and Applications (4 papers), Receptor Mechanisms and Signaling (3 papers), Cardiac electrophysiology and arrhythmias (3 papers), Effects and risks of endocrine disrupting chemicals (3 papers), DNA and Nucleic Acid Chemistry (3 papers) and Thyroid Disorders and Treatments (2 papers). The work is most often cited by research in Health, Toxicology and Mutagenesis (224 citations), Spectroscopy (197 citations), Molecular Biology (700 citations), Biophysics (56 citations) and Small Animals (71 citations). Eric D. Watt has collaborated with scholars based in United States, Denmark and United Kingdom. Frequent co-authors include J. Patrick Loria, Hashim M. Al‐Hashimi, Richard Judson, Qi Zhang, Xiaoyan Sun, Rebecca B. Berlow, Keith A. Houck, Evgenii L. Kovrigin, Hiroko Shimada and Nicolas Doucet. Their work appears in journals such as Toxicological Sciences, Regulatory Toxicology and Pharmacology, Chemical Research in Toxicology, Biophysical Journal 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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