Greg S. B. Suh

4.4k total citations · 2 hit papers
31 papers, 3.0k citations indexed

About

Greg S. B. Suh is a scholar working on Cellular and Molecular Neuroscience, Endocrine and Autonomic Systems and Insect Science. According to data from OpenAlex, Greg S. B. Suh has authored 31 papers receiving a total of 3.0k indexed citations (citations by other indexed papers that have themselves been cited), including 23 papers in Cellular and Molecular Neuroscience, 9 papers in Endocrine and Autonomic Systems and 9 papers in Insect Science. Recurrent topics in Greg S. B. Suh's work include Neurobiology and Insect Physiology Research (23 papers), Insect Utilization and Effects (9 papers) and Circadian rhythm and melatonin (7 papers). Greg S. B. Suh is often cited by papers focused on Neurobiology and Insect Physiology Research (23 papers), Insect Utilization and Effects (9 papers) and Circadian rhythm and melatonin (7 papers). Greg S. B. Suh collaborates with scholars based in United States, South Korea and United Kingdom. Greg S. B. Suh's co-authors include Soohong Min, Monica Dus, S Lawrence Zipursky, Minrong Ai, Raymond J. Deshaies, Gregory A. Cope, L. Aravind, Sylvia E. Schwarz, Eugene V. Koonin and Anne C. Hergarden and has published in prestigious journals such as Nature, Science and Proceedings of the National Academy of Sciences.

In The Last Decade

Greg S. B. Suh

29 papers receiving 2.9k citations

Hit Papers

Role of Predicted Metalloprotease Motif of Jab1/Csn5 in C... 2002 2026 2010 2018 2002 2004 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
Greg S. B. Suh United States 21 1.8k 845 829 672 424 31 3.0k
W. Daniel Tracey United States 21 1.7k 1.0× 705 0.8× 481 0.6× 512 0.8× 229 0.5× 36 2.6k
André Fiala Germany 31 2.6k 1.5× 928 1.1× 1.1k 1.4× 620 0.9× 280 0.7× 60 3.5k
Carlos Ribeiro Portugal 29 1.6k 0.9× 1.2k 1.5× 865 1.0× 1.2k 1.8× 252 0.6× 49 3.8k
Andreas S. Thum Germany 29 1.9k 1.1× 351 0.4× 863 1.0× 511 0.8× 183 0.4× 62 2.3k
Toshihiro Kitamoto United States 31 3.2k 1.8× 1.1k 1.3× 1.3k 1.5× 681 1.0× 628 1.5× 74 4.0k
Serge Birman France 31 2.8k 1.5× 1.1k 1.3× 1.2k 1.4× 777 1.2× 355 0.8× 67 3.8k
Ilona C Grunwald Kadow Germany 21 1.6k 0.9× 395 0.5× 656 0.8× 635 0.9× 135 0.3× 40 2.2k
Liliane Abuin Switzerland 21 2.0k 1.1× 979 1.2× 899 1.1× 735 1.1× 87 0.2× 30 2.6k
Josh Dubnau United States 25 1.8k 1.0× 1.6k 1.9× 926 1.1× 457 0.7× 193 0.5× 47 3.5k
Gerd Bicker Germany 34 2.0k 1.1× 601 0.7× 746 0.9× 740 1.1× 237 0.6× 90 3.1k

Countries citing papers authored by Greg S. B. Suh

Since Specialization
Citations

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

Fields of papers citing papers by Greg S. B. Suh

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Greg S. B. Suh. 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 Greg S. B. Suh. The network helps show where Greg S. B. Suh may publish in the future.

Co-authorship network of co-authors of Greg S. B. Suh

This figure shows the co-authorship network connecting the top 25 collaborators of Greg S. B. Suh. A scholar is included among the top collaborators of Greg S. B. Suh 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 Greg S. B. Suh. Greg S. B. Suh 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.
Kim, Shinhye, Yujin Kim, Se Hoon Kim, et al.. (2025). Encoding the glucose identity by discrete hypothalamic neurons via the gut-brain axis. Neuron. 113(16). 2673–2691.e9.
2.
Lee, Ji Yeon, et al.. (2025). Post ingestive systemic nutrient sensing for whole-body homeostasis. Molecules and Cells. 48(11). 100271–100271.
3.
Kim, Seong-Jin, Kang‐Min Lee, Si Hyung Park, et al.. (2024). A sexually transmitted sugar orchestrates reproductive responses to nutritional stress. Nature Communications. 15(1). 8477–8477. 2 indexed citations
4.
Kim, Byoungsoo, et al.. (2024). Postprandial sodium sensing by enteric neurons in Drosophila. Nature Metabolism. 6(5). 837–846. 5 indexed citations
5.
Oh, Yangkyun & Greg S. B. Suh. (2023). Starvation-induced sleep suppression requires the Drosophila brain nutrient sensor. Journal of Neurogenetics. 37(1-2). 70–77. 6 indexed citations
6.
Lee, Chanhee, Geun Ho Im, Seongyeon Kim, et al.. (2022). General‐Purpose Ultrasound Neuromodulation System for Chronic, Closed‐Loop Preclinical Studies in Freely Behaving Rodents. Advanced Science. 9(34). e2202345–e2202345. 25 indexed citations
7.
Oh, Yangkyun, Jason Sih-Yu Lai, Soohong Min, et al.. (2021). Periphery signals generated by Piezo-mediated stomach stretch and Neuromedin-mediated glucose load regulate the Drosophila brain nutrient sensor. Neuron. 109(12). 1979–1995.e6. 45 indexed citations
8.
Kim, Boram, Makoto I. Kanai, Yangkyun Oh, et al.. (2021). Response of the microbiome–gut–brain axis in Drosophila to amino acid deficit. Nature. 593(7860). 570–574. 70 indexed citations
9.
Min, Soohong, Yangkyun Oh, Pushpa Verma, et al.. (2021). Control of feeding by Piezo-mediated gut mechanosensation in Drosophila. eLife. 10. 47 indexed citations
10.
You, Hye Jin, Jae‐Jin Lee, Kyung‐Ah Lee, et al.. (2020). Identification and characterization of GAL4 drivers that mark distinct cell types and regions in the Drosophila adult gut. Journal of Neurogenetics. 35(1). 33–44. 7 indexed citations
11.
Oh, Yangkyun, Jason Sih-Yu Lai, Hediye Erdjument‐Bromage, et al.. (2019). A glucose-sensing neuron pair regulates insulin and glucagon in Drosophila. Nature. 574(7779). 559–564. 91 indexed citations
12.
Park, Jin‐Yong, Monica Dus, Seonil Kim, et al.. (2016). Drosophila SLC5A11 Mediates Hunger by Regulating K+ Channel Activity. Current Biology. 26(15). 1965–1974. 45 indexed citations
13.
Enjin, Anders, Emanuela E. Zaharieva, Dominic D. Frank, et al.. (2016). Humidity Sensing in Drosophila. Current Biology. 26(10). 1352–1358. 189 indexed citations
14.
Dus, Monica, Jason Sih-Yu Lai, Keith M. Gunapala, et al.. (2015). Nutrient Sensor in the Brain Directs the Action of the Brain-Gut Axis in Drosophila. Neuron. 87(1). 139–151. 172 indexed citations
15.
Qi, Wei, et al.. (2015). A quantitative feeding assay in adult Drosophila reveals rapid modulation of food ingestion by its nutritional value. Molecular Brain. 8(1). 87–87. 39 indexed citations
16.
Dus, Monica, Minrong Ai, & Greg S. B. Suh. (2013). Taste-independent nutrient selection is mediated by a brain-specific Na+/solute co-transporter in Drosophila. Nature Neuroscience. 16(5). 526–528. 84 indexed citations
17.
Ai, Minrong, Soohong Min, Yaël Grosjean, et al.. (2010). Acid sensing by the Drosophila olfactory system. Nature. 468(7324). 691–695. 259 indexed citations
18.
Suh, Greg S. B., et al.. (2007). Light Activation of an Innate Olfactory Avoidance Response in Drosophila. Current Biology. 17(10). 905–908. 105 indexed citations
19.
Cope, Gregory A., Greg S. B. Suh, L. Aravind, et al.. (2002). Role of Predicted Metalloprotease Motif of Jab1/Csn5 in Cleavage of Nedd8 from Cul1. Science. 298(5593). 608–611. 571 indexed citations breakdown →
20.
Suh, Greg S. B., Burkhard Poeck, Tanguy Chouard, et al.. (2002). Drosophila JAB1/CSN5 Acts in Photoreceptor Cells to Induce Glial Cells. Neuron. 33(1). 35–46. 78 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.

Explore authors with similar magnitude of impact

Rankless by CCL
2026