Daniel S. McQueen

98 papers receiving 3.8k citations

Peers

Daniel S. McQueen
Comparison fields: 5 of 115
  • Endocrine and Autonomic Systems 1.2k
  • Sensory Systems 351
  • Cellular and Molecular Neuroscience 1.3k
  • Physiology 1.5k
  • Physiology 270
Replace Sandro Giuliani with:
Sandro Giuliani Italy
Paolo Santicioli Italy
F. Lembeck Austria
Margaret A. Vizzard United States
Derek C. Molliver United States
Fred Lembeck Austria
Miwa Misawa Japan
Gerhard Skofitsch Austria
Debra A. Cockayne United States
Hironobu Yoshimatsu Japan
Daniel S. McQueen relative to Sandro Giuliani Italy Sandro Giuliani's profile →
Citations per field
00.5×2×2.9×
Sandro Giuliani · 1×
Citations per year

Countries citing papers authored by Daniel S. McQueen

Since Specialization
Citations

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

Fields of papers citing papers by Daniel S. McQueen

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 100 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2007250
2 2004195
3 1992167
4 1998135
5 2007122
6 1981112
7 1992112
8 198695
9 198394
10 199192
11 199189
12 199387
13 198386
14 199279
15 198078
16 198077
17 199577
18 199877
19 200571
20 200671

About Daniel S. McQueen

Daniel S. McQueen is a scholar working on Endocrine and Autonomic Systems, Cellular and Molecular Neuroscience, Physiology, Cardiology and Cardiovascular Medicine and Physiology, having authored 100 papers that have together received 4.1k indexed citations. Recurring topics across this work include Neuroscience of respiration and sleep (37 papers), Pain Mechanisms and Treatments (26 papers), Neuropeptides and Animal Physiology (21 papers), Receptor Mechanisms and Signaling (20 papers), Heart Rate Variability and Autonomic Control (14 papers), Sleep and Wakefulness Research (11 papers), Neurobiology and Insect Physiology Research (7 papers) and Nitric Oxide and Endothelin Effects (6 papers). The work is most often cited by research in Endocrine and Autonomic Systems (1.2k citations), Sensory Systems (351 citations), Cellular and Molecular Neuroscience (1.3k citations), Physiology (1.5k citations) and Physiology (270 citations). Daniel S. McQueen has collaborated with scholars based in United Kingdom, Portugal and United States. Frequent co-authors include Joaquim Alexandre Ribeiro, Jonathan R. Seckl, Iain P. Chessell, Lucy Frances Donaldson, Graham J. Birrell, Susan M. Bond, Ainsley Iggo, Blair D. Grubb, Anthony J. Harmar and Jonathan L. Rees. Their work appears in journals such as British Journal of Pharmacology, The Journal of Physiology, European Journal of Pharmacology, British Journal of Clinical Pharmacology and Journal of Cardiovascular Pharmacology.

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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