Ali D. Güler

5.2k total citations · 2 hit papers
45 papers, 3.7k citations indexed

About

Ali D. Güler is a scholar working on Endocrine and Autonomic Systems, Cellular and Molecular Neuroscience and Physiology. According to data from OpenAlex, Ali D. Güler has authored 45 papers receiving a total of 3.7k indexed citations (citations by other indexed papers that have themselves been cited), including 28 papers in Endocrine and Autonomic Systems, 21 papers in Cellular and Molecular Neuroscience and 13 papers in Physiology. Recurrent topics in Ali D. Güler's work include Circadian rhythm and melatonin (20 papers), Neurobiology and Insect Physiology Research (12 papers) and Photoreceptor and optogenetics research (10 papers). Ali D. Güler is often cited by papers focused on Circadian rhythm and melatonin (20 papers), Neurobiology and Insect Physiology Research (12 papers) and Photoreceptor and optogenetics research (10 papers). Ali D. Güler collaborates with scholars based in United States, Türkiye and United Kingdom. Ali D. Güler's co-authors include Michael J. Caterina, Cara M. Altimus, Tohko Iida, Makoto Tominaga, Isao Shimizu, Man‐Kyo Chung, Hyosang Lee, Samer Hattar, Mark W. Hankins and Gurprit S. Lall and has published in prestigious journals such as Nature, Cell and Proceedings of the National Academy of Sciences.

In The Last Decade

Ali D. Güler

43 papers receiving 3.6k citations

Hit Papers

Heat-Evoked Activation of the Ion Channel, TRPV4 2002 2026 2010 2018 2002 2008 250 500 750

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Ali D. Güler United States 22 1.6k 1.5k 1.2k 1.1k 791 45 3.7k
Hyosang Lee South Korea 23 639 0.4× 1.6k 1.1× 2.2k 1.8× 1.3k 1.1× 1.3k 1.6× 44 5.1k
Charles Watson Australia 13 705 0.4× 2.9k 2.0× 230 0.2× 1.2k 1.1× 636 0.8× 22 5.4k
William J. Joiner United States 27 871 0.5× 1.9k 1.3× 209 0.2× 1.7k 1.5× 272 0.3× 39 3.6k
Alexander C. Jackson United States 19 820 0.5× 1.0k 0.7× 372 0.3× 964 0.9× 384 0.5× 23 3.0k
Megumi Hatori United States 20 2.9k 1.8× 723 0.5× 96 0.1× 869 0.8× 2.0k 2.5× 28 4.2k
Gloria Benítez‐King Mexico 29 1.7k 1.1× 627 0.4× 118 0.1× 611 0.6× 528 0.7× 87 2.7k
Jörg H. Stehle Germany 37 3.4k 2.1× 1.7k 1.2× 125 0.1× 1.1k 1.0× 852 1.1× 73 4.9k
Miklós Antal Hungary 33 270 0.2× 2.3k 1.6× 268 0.2× 1.1k 1.0× 799 1.0× 106 4.0k
Aaron D. Laposky United States 20 4.1k 2.6× 443 0.3× 162 0.1× 601 0.5× 3.0k 3.9× 30 5.8k
Maria Beatrice Passani Italy 37 656 0.4× 977 0.7× 899 0.7× 1.7k 1.6× 400 0.5× 101 3.8k

Countries citing papers authored by Ali D. Güler

Since Specialization
Citations

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

Fields of papers citing papers by Ali D. Güler

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Ali D. Güler. 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 Ali D. Güler. The network helps show where Ali D. Güler may publish in the future.

Co-authorship network of co-authors of Ali D. Güler

This figure shows the co-authorship network connecting the top 25 collaborators of Ali D. Güler. A scholar is included among the top collaborators of Ali D. Güler 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 Ali D. Güler. Ali D. Güler 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.
Arslan, Burak, et al.. (2025). The Significance of Circulating Basophils as Predictors of Tumor Aggressiveness in Clear‐Cell Renal Cell Carcinoma. Asia-Pacific Journal of Clinical Oncology. 22(1). 122–128.
3.
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
4.
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
5.
Spano, Anthony, et al.. (2022). Food-induced dopamine signaling in AgRP neurons promotes feeding. Cell Reports. 41(9). 111718–111718. 16 indexed citations
6.
Güler, Ali D., et al.. (2022). Local Drd1-neurons input to subgroups of arcuate AgRP/NPY-neurons. iScience. 25(7). 104605–104605. 7 indexed citations
7.
Güler, Ali D., et al.. (2022). A Building Block-Based Beam-Break (B 5 ) Locomotor Activity Monitoring System and Its Use in Circadian Biology Research. BioTechniques. 73(2). 104–109. 2 indexed citations
8.
Güler, Ali D., et al.. (2021). Long-term high fat diet consumption reversibly alters feeding behavior via a dopamine-associated mechanism in mice. Behavioural Brain Research. 414. 113470–113470. 13 indexed citations
9.
Güler, Ali D., et al.. (2021). Metabolic homeostasis via BDNF and its receptors. Trends in Endocrinology and Metabolism. 32(7). 488–499. 62 indexed citations
11.
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
12.
Güler, Ali D., Yeliz Pekçevik, Hakan Türkön, et al.. (2018). Is elevated urotensin II level a predictor for increased cardiovascular risk in subjects with acromegaly?. Journal of Endocrinological Investigation. 42(2). 207–215. 5 indexed citations
13.
Grippo, Ryan M., et al.. (2017). Direct Midbrain Dopamine Input to the Suprachiasmatic Nucleus Accelerates Circadian Entrainment. Current Biology. 27(16). 2465–2475.e3. 103 indexed citations
14.
Moraes, Maria Nathália, Leonardo Vinícius Monteiro de Assis, Felipe Henriques, et al.. (2017). Cold-sensing TRPM8 channel participates in circadian control of the brown adipose tissue. Biochimica et Biophysica Acta (BBA) - Molecular Cell Research. 1864(12). 2415–2427. 28 indexed citations
15.
Warthen, Daniel M., Matteo Ottolini, Yingtang Shi, et al.. (2016). Activation of Pyramidal Neurons in Mouse Medial Prefrontal Cortex Enhances Food-Seeking Behavior While Reducing Impulsivity in the Absence of an Effect on Food Intake. Frontiers in Behavioral Neuroscience. 10. 63–63. 35 indexed citations
16.
Wheeler, Michael A., Cody J. Smith, Matteo Ottolini, et al.. (2016). Genetically targeted magnetic control of the nervous system. Nature Neuroscience. 19(5). 756–761. 172 indexed citations
17.
Walker, M., Alan C. Rupp, Rebecca Elsaesser, et al.. (2015). RdgB2 is required for dim-light input into intrinsically photosensitive retinal ganglion cells. Molecular Biology of the Cell. 26(20). 3671–3678. 8 indexed citations
18.
Güler, Ali D., Jennifer L. Ecker, Gurprit S. Lall, et al.. (2008). Melanopsin cells are the principal conduits for rod–cone input to non-image-forming vision. Nature. 453(7191). 102–105. 652 indexed citations breakdown →
19.
Ecker, Jennifer L., Ali D. Güler, Robert J. Lucas, & Samer Hattar. (2007). Genetic Ablation of Melanopsin-Containing Retinal Ganglion Cells Severely Attenuates Light-Dependent Physiological Functions. Investigative Ophthalmology & Visual Science. 48(13). 2989–2989. 1 indexed citations
20.
Xu, Haiyan, Jiro Hirosumi, K. Teoman Uysal, Ali D. Güler, & Gökhan S. Hotamışlıgil. (2002). Exclusive Action of Transmembrane TNFα in Adipose Tissue Leads to Reduced Adipose Mass and Local But Not Systemic Insulin Resistance. Endocrinology. 143(4). 1502–1511. 81 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