John N. Campbell

3.6k total citations · 1 hit paper
34 papers, 2.5k citations indexed

About

John N. Campbell is a scholar working on Endocrine and Autonomic Systems, Molecular Biology and Cellular and Molecular Neuroscience. According to data from OpenAlex, John N. Campbell has authored 34 papers receiving a total of 2.5k indexed citations (citations by other indexed papers that have themselves been cited), including 18 papers in Endocrine and Autonomic Systems, 10 papers in Molecular Biology and 9 papers in Cellular and Molecular Neuroscience. Recurrent topics in John N. Campbell's work include Regulation of Appetite and Obesity (10 papers), Biochemical Analysis and Sensing Techniques (7 papers) and Circadian rhythm and melatonin (6 papers). John N. Campbell is often cited by papers focused on Regulation of Appetite and Obesity (10 papers), Biochemical Analysis and Sensing Techniques (7 papers) and Circadian rhythm and melatonin (6 papers). John N. Campbell collaborates with scholars based in United States, United Kingdom and Denmark. John N. Campbell's co-authors include Robert H. LaMotte, Bradford B. Lowell, Joseph C. Madara, Jon M. Resch, Henning Fenselau, Linus Tsai, Anne M.J. Verstegen, Bhavik P. Shah, Michael J. Krashes and Alastair S. Garfield and has published in prestigious journals such as Journal of Clinical Investigation, Nature Communications and Neuron.

In The Last Decade

John N. Campbell

32 papers receiving 2.5k citations

Hit Papers

A molecular census of arcuate hypothalamus and median emi... 2017 2026 2020 2023 2017 100 200 300 400 500

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
John N. Campbell United States 20 1.3k 879 503 493 471 34 2.5k
Jon M. Resch United States 17 919 0.7× 637 0.7× 350 0.7× 430 0.9× 377 0.8× 36 2.1k
Henning Fenselau Germany 16 964 0.7× 550 0.6× 383 0.8× 466 0.9× 350 0.7× 27 2.0k
Fanny Langlet France 20 1.2k 0.9× 645 0.7× 385 0.8× 545 1.1× 251 0.5× 30 2.3k
Shane T. Hentges United States 26 1.0k 0.8× 510 0.6× 582 1.2× 605 1.2× 651 1.4× 51 2.4k
Shigetomo Suyama Japan 16 1.0k 0.8× 588 0.7× 349 0.7× 406 0.8× 239 0.5× 23 1.8k
Gina M. Leinninger United States 31 1.9k 1.5× 970 1.1× 801 1.6× 671 1.4× 758 1.6× 56 3.3k
Shuichi Koda Japan 13 2.0k 1.5× 1.1k 1.3× 1.0k 2.0× 431 0.9× 683 1.5× 18 2.9k
Chia Li United States 23 988 0.8× 612 0.7× 392 0.8× 483 1.0× 992 2.1× 38 2.4k
Jong‐Woo Sohn South Korea 26 1.2k 0.9× 788 0.9× 538 1.1× 671 1.4× 407 0.9× 60 2.6k
Joseph C. Madara United States 22 1.8k 1.3× 793 0.9× 673 1.3× 358 0.7× 659 1.4× 29 2.8k

Countries citing papers authored by John N. Campbell

Since Specialization
Citations

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

Fields of papers citing papers by John N. Campbell

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by John N. Campbell. 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 John N. Campbell. The network helps show where John N. Campbell may publish in the future.

Co-authorship network of co-authors of John N. Campbell

This figure shows the co-authorship network connecting the top 25 collaborators of John N. Campbell. A scholar is included among the top collaborators of John N. Campbell 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 John N. Campbell. John N. Campbell 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
1.
Liu, Yuanming, Chen Chen, Lü Yang, et al.. (2025). Co-Conservation of synaptic gene expression and circuitry in collicular neurons. Nature Communications. 16(1). 9146–9146.
2.
Li, Chia, Damien Kerspern, Dylan M. Rausch, et al.. (2024). Molecular connectomics reveals a glucagon-like peptide 1-sensitive neural circuit for satiety. Nature Metabolism. 6(12). 2354–2373. 20 indexed citations
3.
Stornetta, Daniel S., et al.. (2024). Molecular Organization of Autonomic, Respiratory, and Spinally-Projecting Neurons in the Mouse Ventrolateral Medulla. Journal of Neuroscience. 44(31). e2211232024–e2211232024. 3 indexed citations
4.
Abbott, Stephen B.G., et al.. (2023). Molecular cell types as functional units of the efferent vagus nerve. Seminars in Cell and Developmental Biology. 156. 210–218. 5 indexed citations
5.
Deppmann, Christopher D., et al.. (2023). Leptin receptor neurons in the dorsomedial hypothalamus input to the circadian feeding network. Science Advances. 9(34). eadh9570–eadh9570. 8 indexed citations
6.
Liu, Yuanming, Élise Savier, Victor J. DePiero, et al.. (2023). Mapping visual functions onto molecular cell types in the mouse superior colliculus. Neuron. 111(12). 1876–1886.e5. 21 indexed citations
7.
Gupta, Deepali, Kripa Shankar, Salil Varshney, et al.. (2023). Ghrelin deletion and conditional ghrelin cell ablation increase pancreatic islet size in mice. Journal of Clinical Investigation. 133(24). 2 indexed citations
8.
Spano, Anthony, et al.. (2022). Food-induced dopamine signaling in AgRP neurons promotes feeding. Cell Reports. 41(9). 111718–111718. 16 indexed citations
9.
Wu, Chen, et al.. (2022). Genetic encoding of an esophageal motor circuit. Cell Reports. 39(11). 110962–110962. 21 indexed citations
10.
11.
Merino, Jordi, Hassan S. Dashti, Chloé Sarnowski, et al.. (2021). Genetic analysis of dietary intake identifies new loci and functional links with metabolic traits. Nature Human Behaviour. 6(1). 155–163. 27 indexed citations
12.
Campbell, John N., et al.. (2021). Highly selective brain-to-gut communication via genetically defined vagus neurons. Neuron. 109(13). 2106–2115.e4. 66 indexed citations
13.
Todd, William D., Anne Venner, Christelle Anaclet, et al.. (2020). Suprachiasmatic VIP neurons are required for normal circadian rhythmicity and comprised of molecularly distinct subpopulations. Nature Communications. 11(1). 4410–4410. 91 indexed citations
14.
Grippo, Ryan M., Laura M. Sipe, Aarti M. Purohit, et al.. (2020). Dopamine Signaling in the Suprachiasmatic Nucleus Enables Weight Gain Associated with Hedonic Feeding. Current Biology. 30(2). 196–208.e8. 33 indexed citations
15.
Li, Monica M., Joseph C. Madara, Jennifer S. Steger, et al.. (2019). The Paraventricular Hypothalamus Regulates Satiety and Prevents Obesity via Two Genetically Distinct Circuits. Neuron. 102(3). 653–667.e6. 144 indexed citations
16.
Resch, Jon M., Henning Fenselau, Joseph C. Madara, et al.. (2017). Aldosterone-Sensing Neurons in the NTS Exhibit State-Dependent Pacemaker Activity and Drive Sodium Appetite via Synergy with Angiotensin II Signaling. Neuron. 96(1). 190–206.e7. 73 indexed citations
17.
Garfield, Alastair S., Bhavik P. Shah, Christian R. Burgess, et al.. (2016). Dynamic GABAergic afferent modulation of AgRP neurons. Nature Neuroscience. 19(12). 1628–1635. 166 indexed citations
18.
Garfield, Alastair S., Chia Li, Joseph C. Madara, et al.. (2015). A neural basis for melanocortin-4 receptor–regulated appetite. Nature Neuroscience. 18(6). 863–871. 325 indexed citations
20.
LaMotte, Robert H. & John N. Campbell. (1978). Comparison of responses of warm and nociceptive C-fiber afferents in monkey with human judgments of thermal pain. Journal of Neurophysiology. 41(2). 509–528. 332 indexed citations

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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