Daniel W. Nuno

1000 citations
24 papers · 840 indexed · h-index 14

Impact in

Papers in

Daniel W. Nuno

24 papers receiving 835 citations

Peers

Daniel W. Nuno
Comparison fields: 5 of 77
  • Cardiology and Cardiovascular Medicine 300
  • Physiology 340
  • Cellular and Molecular Neuroscience 168
  • Biochemistry 66
  • Sensory Systems 37
Replace Pilar Cidad with:
Pilar Cidad Spain
Ibolya Rutkai United States
Sara Benedito Spain
Giuseppe Cifelli Italy
Kazuhide Nishimaru Japan
Greg G. Geary United States
Preet S. Chadha Australia
Stephanie E. Wölfle Germany
Manoj C. Rodrigo United States
Hassibullah Akeefe United States
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Citations per field
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Citations per year

Countries citing papers authored by Daniel W. Nuno

Since Specialization
Citations

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

Fields of papers citing papers by Daniel W. Nuno

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Daniel W. Nuno. 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 Daniel W. Nuno. The network helps show where Daniel W. Nuno may publish in the future.

Co-authors

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

All Works

20 of 20 papers shown
#Work
1 202211
2 20194
3 20187
4 201734
5 20166
6 201535
7 201330
8 201212
9 201248
10 201213
11 201014
12 200930
13 200454
14 200092
15 199946
16 19919
17 19901
18 19906
19 198825
20 19881

About Daniel W. Nuno

Daniel W. Nuno is a scholar working on Cardiology and Cardiovascular Medicine, Physiology, Molecular Biology, Cell Biology and Endocrinology, Diabetes and Metabolism, having authored 24 papers that have together received 840 indexed citations. Recurring topics across this work include Nitric Oxide and Endothelin Effects (14 papers), Receptor Mechanisms and Signaling (7 papers), Renin-Angiotensin System Studies (6 papers), Caveolin-1 and cellular processes (3 papers), Cardiac Arrhythmias and Treatments (2 papers), Protein Kinase Regulation and GTPase Signaling (2 papers), Cholesterol and Lipid Metabolism (2 papers) and Ion channel regulation and function (2 papers). The work is most often cited by research in Cardiology and Cardiovascular Medicine (300 citations), Physiology (340 citations), Cellular and Molecular Neuroscience (168 citations), Biochemistry (66 citations) and Sensory Systems (37 citations). Daniel W. Nuno has collaborated with scholars based in United States and Portugal. Frequent co-authors include Kathryn G. Lamping, Frank M. Faraci, Sarah K. England, Robert M. Weiss, Curt D. Sigmund, Rita Barresi, Kevin P. Campbell, Leanne L. Cribbs, Sally Prouty and Julie L. Lavoie. Their work appears in journals such as American Journal of Physiology-Heart and Circulatory Physiology, Journal of the American Heart Association, Arteriosclerosis Thrombosis and Vascular Biology, American Journal of Physiology-Regulatory, Integrative and Comparative Physiology and Journal of Hypertension.

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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