S.L. Dun

2.8k citations
45 papers · 2.5k · h-index 28

Impact in

Papers in

S.L. Dun

44 papers receiving 2.4k citations

Peers

S.L. Dun
Comparison fields: 5 of 84
  • Endocrine and Autonomic Systems 900
  • Cellular and Molecular Neuroscience 1.1k
  • Physiology 1.1k
  • Behavioral Neuroscience 135
  • Reproductive Medicine 238
Replace Tanemichi Chiba with:
Tanemichi Chiba Japan
V. John Massari United States
Sue A. Aicher United States
T. Ho ̈kfelt Sweden
Brian Choi United States
R. Quirion Canada
A.A. Sluiter Netherlands
Shirley A. Joseph United States
Jong‐Woo Sohn South Korea
Bang H. Hwang United States
S.L. Dun relative to Tanemichi Chiba Japan Tanemichi Chiba's profile →
Citations per field
00.5×2×3.1×
Tanemichi Chiba · 1×
Citations per year

Countries citing papers authored by S.L. Dun

Since Specialization
Citations

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

Fields of papers citing papers by S.L. Dun

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 45 papers — load more, or switch the sort, to bring in the rest.

#Work
1 1993257
2 2013196
3 1992180
4 1994177
5 1999156
6 2012150
7 1999112
8 199483
9 199382
10 199776
11 199376
12 200072
13 201364
14 199260
15 200158
16 199948
17 200042
18 199641
19 199240
20 199939

About S.L. Dun

S.L. Dun is a scholar working on Cellular and Molecular Neuroscience, Physiology, Endocrine and Autonomic Systems, Molecular Biology and Reproductive Medicine, having authored 45 papers that have together received 2.5k indexed citations. Recurring topics across this work include Neuropeptides and Animal Physiology (17 papers), Receptor Mechanisms and Signaling (10 papers), Neuroscience of respiration and sleep (10 papers), Nitric Oxide and Endothelin Effects (9 papers), Neuroscience and Neuropharmacology Research (8 papers), Pain Mechanisms and Treatments (7 papers), Hypothalamic control of reproductive hormones (5 papers) and Regulation of Appetite and Obesity (5 papers). The work is most often cited by research in Endocrine and Autonomic Systems (900 citations), Cellular and Molecular Neuroscience (1.1k citations), Physiology (1.1k citations), Behavioral Neuroscience (135 citations) and Reproductive Medicine (238 citations). S.L. Dun has collaborated with scholars based in United States, Germany and Hong Kong. Frequent co-authors include Nae J. Dun, Ulrich Förstermann, J.K. Chang, Su‐Ying Wu, L F Tseng, Ernest H. Kwok, Rong‐Ming Lyu, Harald Schmidt, Jin Jun Luo and Yu‐Hsin Chen. Their work appears in journals such as Neuroscience, Brain Research, Journal of Neuroendocrinology, New Phytologist and Journal of Biomedical Science.

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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