Jun Ding

9.9k total citations · 2 hit papers
70 papers, 6.8k citations indexed

About

Jun Ding is a scholar working on Cellular and Molecular Neuroscience, Molecular Biology and Biomedical Engineering. According to data from OpenAlex, Jun Ding has authored 70 papers receiving a total of 6.8k indexed citations (citations by other indexed papers that have themselves been cited), including 48 papers in Cellular and Molecular Neuroscience, 21 papers in Molecular Biology and 18 papers in Biomedical Engineering. Recurrent topics in Jun Ding's work include Neuroscience and Neuropharmacology Research (30 papers), Neuroscience and Neural Engineering (20 papers) and Muscle activation and electromyography studies (15 papers). Jun Ding is often cited by papers focused on Neuroscience and Neuropharmacology Research (30 papers), Neuroscience and Neural Engineering (20 papers) and Muscle activation and electromyography studies (15 papers). Jun Ding collaborates with scholars based in United States, China and Switzerland. Jun Ding's co-authors include D. James Surmeier, Bernardo L. Sabatini, Zhongfeng Wang, Michelle Day, Weixing Shen, Stuart A. Binder‐Macleod, Anthony S. Wexler, Nicolas X. Tritsch, Joshua A. Goldberg and Giorgio Bernardi and has published in prestigious journals such as Nature, Science and Cell.

In The Last Decade

Jun Ding

69 papers receiving 6.7k citations

Hit Papers

D1 and D2 dopamine-receptor modulation of striatal glutam... 2006 2026 2012 2019 2007 2006 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
Jun Ding United States 40 4.5k 2.1k 1.9k 1.5k 738 70 6.8k
Kimberly R. Thompson United States 18 4.6k 1.0× 1.6k 0.7× 2.1k 1.1× 724 0.5× 636 0.9× 20 6.2k
Hirotaka Onoe Japan 43 1.9k 0.4× 2.5k 1.2× 1.5k 0.8× 483 0.3× 576 0.8× 171 7.0k
Hiroyuki Hioki Japan 36 3.0k 0.7× 1.7k 0.8× 1.8k 1.0× 579 0.4× 237 0.3× 93 5.4k
Minmin Luo China 49 3.9k 0.9× 1.8k 0.9× 2.2k 1.2× 260 0.2× 534 0.7× 103 7.3k
Vikaas S. Sohal United States 38 5.4k 1.2× 2.1k 1.0× 5.0k 2.7× 349 0.2× 413 0.6× 88 8.7k
Alexxai V. Kravitz United States 31 3.3k 0.7× 1.3k 0.6× 1.8k 1.0× 1.0k 0.7× 225 0.3× 69 5.2k
José L. Lanciego Spain 49 3.5k 0.8× 1.9k 0.9× 1.3k 0.7× 2.2k 1.5× 134 0.2× 143 7.1k
Lin Tian United States 39 5.2k 1.1× 3.4k 1.6× 2.5k 1.4× 253 0.2× 473 0.6× 98 8.5k
Thomas Kuner Germany 53 4.8k 1.1× 3.9k 1.8× 1.4k 0.8× 226 0.2× 461 0.6× 124 7.9k
Thomas S. Otis United States 41 4.9k 1.1× 3.2k 1.5× 1.8k 1.0× 607 0.4× 136 0.2× 69 6.5k

Countries citing papers authored by Jun Ding

Since Specialization
Citations

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

Fields of papers citing papers by Jun Ding

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jun Ding

This figure shows the co-authorship network connecting the top 25 collaborators of Jun Ding. A scholar is included among the top collaborators of Jun Ding 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 Jun Ding. Jun Ding 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.
Roth, Richard H., et al.. (2025). Remodelling of corticostriatal axonal boutons during motor learning. Nature. 646(8083). 143–151. 1 indexed citations
2.
Ding, Xinlu, Daniel N. Silverman, Peng Zhong, et al.. (2025). Neuroendocrine circuit for sleep-dependent growth hormone release. Cell. 188(18). 4968–4979.e12. 3 indexed citations
3.
Zhao, Eric T., et al.. (2024). Multiplexed neurochemical sensing with sub-nM sensitivity across 2.25 mm2 area. Biosensors and Bioelectronics. 261. 116474–116474. 1 indexed citations
4.
Xin, Wendy, Megumi Kaneko, Richard H. Roth, et al.. (2024). Oligodendrocytes and myelin limit neuronal plasticity in visual cortex. Nature. 633(8031). 856–863. 20 indexed citations
5.
Roth, Richard H. & Jun Ding. (2024). Cortico-basal ganglia plasticity in motor learning. Neuron. 112(15). 2486–2502. 12 indexed citations
6.
Li, Liang, Yue Sun, Sahil Shah, et al.. (2023). Mettl14-mediated m6A modification ensures the cell-cycle progression of late-born retinal progenitor cells. Cell Reports. 42(6). 112596–112596. 5 indexed citations
7.
Albarran, Eddy, Yue Sun, Karthik Raju, et al.. (2023). Postsynaptic synucleins mediate endocannabinoid signaling. Nature Neuroscience. 26(6). 997–1007. 23 indexed citations
8.
Roth, Richard H., et al.. (2022). Motor learning selectively strengthens cortical and striatal synapses of motor engram neurons. Neuron. 110(17). 2790–2801.e5. 52 indexed citations
9.
Ma, Lei, Michael A. Muniak, Maozhen Qin, et al.. (2022). Locomotion activates PKA through dopamine and adenosine in striatal neurons. Nature. 611(7937). 762–768. 39 indexed citations
10.
Lin, Cheng‐Hui, Yue Sun, Candace S. Y. Chan, et al.. (2022). Identification of cis-regulatory modules for adeno-associated virus-based cell-type-specific targeting in the retina and brain. Journal of Biological Chemistry. 298(4). 101674–101674. 3 indexed citations
11.
Oh, Byeongtaek, et al.. (2021). Modulating the Electrical and Mechanical Microenvironment to Guide Neuronal Stem Cell Differentiation. Advanced Science. 8(7). 2002112–2002112. 46 indexed citations
12.
Kebschull, Justus M., Ethan B. Richman, Drew Friedmann, et al.. (2020). Cerebellar nuclei evolved by repeatedly duplicating a conserved cell-type set. Science. 370(6523). 129 indexed citations
13.
Roth, Richard H. & Jun Ding. (2020). From Neurons to Cognition: Technologies for Precise Recording of Neural Activity Underlying Behavior. SHILAP Revista de lepidopterología. 2020. 7190517–7190517. 10 indexed citations
14.
Puighermanal, Emma, Anna Esteve‐Codina, Su Melser, et al.. (2020). Functional and molecular heterogeneity of D2R neurons along dorsal ventral axis in the striatum. Nature Communications. 11(1). 1957–1957. 39 indexed citations
15.
Obaid, Abdulmalik, Mina-Elraheb Hanna, Yu‐Wei Wu, et al.. (2020). Massively parallel microwire arrays integrated with CMOS chips for neural recording. Science Advances. 6(12). eaay2789–eaay2789. 133 indexed citations
16.
Kim, Jae‐Ick, Sarah Luo, Yu‐Wei Wu, et al.. (2015). Aldehyde dehydrogenase 1a1 mediates a GABA synthesis pathway in midbrain dopaminergic neurons. Science. 350(6256). 102–106. 155 indexed citations
17.
Ding, Jun, Ursula Loizides‐Mangold, Gianpaolo Rando, et al.. (2013). The Peroxisomal Enzyme L-PBE Is Required to Prevent the Dietary Toxicity of Medium-Chain Fatty Acids. Cell Reports. 5(1). 248–258. 46 indexed citations
18.
Ding, Jun, Kevin Takasaki, & Bernardo L. Sabatini. (2009). Supraresolution Imaging in Brain Slices using Stimulated-Emission Depletion Two-Photon Laser Scanning Microscopy. Neuron. 63(4). 429–437. 130 indexed citations
19.
Surmeier, D. James, Jun Ding, Michelle Day, Zhongfeng Wang, & Weixing Shen. (2007). D1 and D2 dopamine-receptor modulation of striatal glutamatergic signaling in striatal medium spiny neurons. Trends in Neurosciences. 30(5). 228–235. 861 indexed citations breakdown →
20.
Wang, Zhongfeng, Kai Li, Michelle Day, et al.. (2006). Dopaminergic Control of Corticostriatal Long-Term Synaptic Depression in Medium Spiny Neurons Is Mediated by Cholinergic Interneurons. Neuron. 50(3). 443–452. 400 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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