Stephen M. Husbands

5.1k citations
157 papers · 4.0k indexed · 1 hit paper · h-index 33
Topics
Neuropeptides and Animal Physiology (82 papers)Receptor Mechanisms and Signaling (73 papers)Pharmacological Receptor Mechanisms and Effects (51 papers)

In The Last Decade

Stephen M. Husbands

156 papers receiving 4.0k citations

Hit Papers

Structural insights into µ-opioid receptor activation20152026201820222015200400600

Peers

Stephen M. Husbands
Comparison fields: 5 of 108
  • Molecular Biology 2.7k
  • Cellular and Molecular Neuroscience 2.5k
  • Physiology 720
  • Organic Chemistry 419
  • Pharmacology 296
Replace Theresa Kopajtic with:
Theresa Kopajtic United States
Lee‐Yuan Liu‐Chen United States
Arthur E. Jacobson United States
John R. Traynor United States
F. Ivy Carroll United States
Florence Noble France
W Gommeren Belgium
Robert A. Lahti United States
Lawrence Toll United States
Peter Brust Germany
Stephen M. Husbands relative to Theresa Kopajtic United States Theresa Kopajtic's profile →
Citations per field
00.5×3.4×
Theresa Kopajtic · 1×
Citations per year

Countries citing papers authored by Stephen M. Husbands

Since Specialization
Citations

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

Fields of papers citing papers by Stephen M. Husbands

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Stephen M. Husbands. 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 Stephen M. Husbands. The network helps show where Stephen M. Husbands may publish in the future.

Co-authorship network of co-authors of Stephen M. Husbands

This figure shows the co-authorship network connecting the top 25 collaborators of Stephen M. Husbands. A scholar is included among the top collaborators of Stephen M. Husbands based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Stephen M. Husbands. Stephen M. Husbands is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
#WorkIndexed citations
1 2
2 9
3 8
4 5
5 1
6 9
7 137
8 86
9 14
10
Structural insights into µ-opioid receptor activationbreakdown →
700
11 27
12 2
13 54
14 70
15 56
16 17
17 46
18 32
19 9
20 9

About Stephen M. Husbands

Stephen M. Husbands is a scholar working on Cellular and Molecular Neuroscience, Toxicology and Molecular Biology, having authored 157 papers that have together received 4.0k indexed citations. Recurring topics across this work include Neuropeptides and Animal Physiology (82 papers), Receptor Mechanisms and Signaling (73 papers) and Pharmacological Receptor Mechanisms and Effects (51 papers). The work is most often cited by research in Cellular and Molecular Neuroscience (2.5k citations), Molecular Biology (2.7k citations) and Toxicology (117 citations). Stephen M. Husbands has collaborated with scholars based in United Kingdom, United States and France. Frequent co-authors include John W. Lewis, John R. Traynor, Mei‐Chuan Ko, David Nutt, Alan L. Hudson, Gerta Cami‐Kobeci, Amy Hauck Newman, Christopher Bailey, Robin J. Tyacke and James H. Woods. Their work appears in journals such as Nature, Proceedings of the National Academy of Sciences and NeuroImage.

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.

Explore authors with similar magnitude of impact

Rankless by CCL
2026