Caroline Nunn

1.2k citations
26 papers · 970 indexed · h-index 18

Caroline Nunn

25 papers receiving 959 citations

Peers

Caroline Nunn
Comparison fields: 5 of 89
  • Cellular and Molecular Neuroscience 274
  • Molecular Biology 650
  • Endocrine and Autonomic Systems 56
  • Endocrinology, Diabetes and Metabolism 137
  • Developmental Neuroscience 26
Replace Sandra Siehler with:
Sandra Siehler Switzerland
Alexander J. Lakhter United States
Georg von Jonquières Australia
Katarina Bedecs Sweden
Katsuro Iwase Japan
Karin Mörl Germany
Manuela Pfeiffer Germany
Alessandra Baragli Italy
Isabelle Coupry France
Francis Castets France
Caroline Nunn relative to Sandra Siehler Switzerland Sandra Siehler's profile →
Citations per field
00.5×1.5×
Sandra Siehler · 1×
Citations per year

Countries citing papers authored by Caroline Nunn

Since Specialization
Citations

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

Fields of papers citing papers by Caroline Nunn

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Caroline Nunn. 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 Caroline Nunn. The network helps show where Caroline Nunn may publish in the future.

Co-authorship network

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

All Works

20 of 20 papers shown
#Work
1 201215
2 201125
3 200766
4 200636
5 200655
6 20057
7 2005205
8 200418
9 200428
10 200313
11 200337
12 200333
13 200291
14 200229
15 200222
16
Functional expression and pharmacological characterisation of the goldfish somatostatin sst5 receptor
20012
17 200110
18 200020
19 200034
20 19909

About Caroline Nunn

Caroline Nunn is a scholar working on Epidemiology, Endocrinology, Diabetes and Metabolism and Molecular Biology, having authored 26 papers that have together received 970 indexed citations. Recurring topics across this work include Neuroendocrine Tumor Research Advances (15 papers), Receptor Mechanisms and Signaling (15 papers), Protein Kinase Regulation and GTPase Signaling (6 papers), Pituitary Gland Disorders and Treatments (4 papers), Ion channel regulation and function (3 papers), Neuropeptides and Animal Physiology (3 papers), Neuroblastoma Research and Treatments (2 papers) and Cardiomyopathy and Myosin Studies (2 papers). The work is most often cited by research in Cellular and Molecular Neuroscience (274 citations), Molecular Biology (650 citations) and Endocrine and Autonomic Systems (56 citations). Caroline Nunn has collaborated with scholars based in Switzerland, Canada and United States. Frequent co-authors include Peter Chidiac, Daniël Hoyer, Anju A. Roy, Daniel Langenegger, Jason Hannon, Dominik Feuerbach, Konstanze Hurth, Sandra Siehler, Dominique Fehlmann and Min‐Xu Zou. Their work appears in journals such as Journal of Biological Chemistry, Circulation Research and Biochemical and Biophysical Research Communications.

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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