Michael X. Zhu

18.1k total citations · 2 hit papers
232 papers, 13.5k citations indexed

About

Michael X. Zhu is a scholar working on Sensory Systems, Molecular Biology and Cellular and Molecular Neuroscience. According to data from OpenAlex, Michael X. Zhu has authored 232 papers receiving a total of 13.5k indexed citations (citations by other indexed papers that have themselves been cited), including 119 papers in Sensory Systems, 106 papers in Molecular Biology and 60 papers in Cellular and Molecular Neuroscience. Recurrent topics in Michael X. Zhu's work include Ion Channels and Receptors (118 papers), Ion channel regulation and function (69 papers) and Neurobiology and Insect Physiology Research (36 papers). Michael X. Zhu is often cited by papers focused on Ion Channels and Receptors (118 papers), Ion channel regulation and function (69 papers) and Neurobiology and Insect Physiology Research (36 papers). Michael X. Zhu collaborates with scholars based in United States, China and United Kingdom. Michael X. Zhu's co-authors include Jisen Tang, Hongzhen Hu, Chunbo Wang, Lutz Birnbaumer, Yakang Lin, Jinbin Tian, Rui Xiao, Veit Flockerzi, Craig K. Colton and Jackie D. Wood and has published in prestigious journals such as Nature, Science and Cell.

In The Last Decade

Michael X. Zhu

227 papers receiving 13.4k citations

Hit Papers

NAADP mobilizes calcium f... 2009 2026 2014 2020 2009 2012 200 400 600

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Michael X. Zhu United States 65 6.5k 6.2k 3.2k 2.9k 1.5k 232 13.5k
Donald L. Gill United States 66 6.9k 1.1× 7.8k 1.3× 4.3k 1.4× 1.1k 0.4× 1.4k 1.0× 134 13.3k
Murali Prakriya United States 45 6.3k 1.0× 5.2k 0.8× 3.8k 1.2× 839 0.3× 980 0.7× 81 11.2k
Haoxing Xu United States 53 3.5k 0.5× 4.5k 0.7× 1.9k 0.6× 4.4k 1.5× 2.0k 1.4× 97 12.5k
Natalia Prevarskaya France 63 4.7k 0.7× 6.8k 1.1× 2.2k 0.7× 749 0.3× 932 0.6× 192 11.4k
Reinhold Penner United States 66 10.2k 1.6× 9.1k 1.5× 5.1k 1.6× 2.2k 0.8× 1.6k 1.1× 129 18.5k
Thomas Gudermann Germany 69 6.3k 1.0× 7.6k 1.2× 4.1k 1.3× 615 0.2× 2.0k 1.4× 317 17.2k
Michael Schaefer Germany 54 4.0k 0.6× 4.5k 0.7× 2.0k 0.6× 776 0.3× 1.2k 0.8× 131 9.5k
Günter Schultz Germany 67 5.3k 0.8× 8.8k 1.4× 4.5k 1.4× 907 0.3× 3.0k 2.0× 148 15.3k
Gary S. Bird United States 51 4.4k 0.7× 4.9k 0.8× 3.1k 1.0× 759 0.3× 939 0.6× 109 8.8k
Indu S. Ambudkar United States 57 5.0k 0.8× 4.7k 0.8× 2.4k 0.8× 554 0.2× 1.6k 1.1× 172 9.3k

Countries citing papers authored by Michael X. Zhu

Since Specialization
Citations

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

Fields of papers citing papers by Michael X. Zhu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Michael X. Zhu. 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 Michael X. Zhu. The network helps show where Michael X. Zhu may publish in the future.

Co-authorship network of co-authors of Michael X. Zhu

This figure shows the co-authorship network connecting the top 25 collaborators of Michael X. Zhu. A scholar is included among the top collaborators of Michael X. Zhu 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 Michael X. Zhu. Michael X. Zhu 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.
Moore, Travis I., Insuk So, Marc Freichel, et al.. (2025). TRPC4 regulates limbic behavior and neuronal development by stabilizing dendrite branches through actomyosin-driven integrin activation. Proceedings of the National Academy of Sciences. 122(33). e2511037122–e2511037122.
2.
Chen, Xiaoying, Xue Zhang, Ming Li, et al.. (2025). Mechanism of capsaicin entry into buried vanilloid sites in TRPV1. Nature Chemical Biology. 21(12). 1957–1969. 4 indexed citations
3.
Koeltzow, Timothy E., et al.. (2024). Transcriptomic Profile Analysis of Brain Tissue in the Absence of Functional TRPM8 Calcium Channel. Biomedicines. 13(1). 75–75.
4.
Weng, Weiji, Xiaokun Gu, Yang Yang, et al.. (2023). N-terminal α-amino SUMOylation of cofilin-1 is critical for its regulation of actin depolymerization. Nature Communications. 14(1). 5688–5688. 13 indexed citations
6.
Qi, Xin, Fan Liu, Qin Hu, et al.. (2022). ASIC1a senses lactate uptake to regulate metabolism in neurons. Redox Biology. 51. 102253–102253. 19 indexed citations
7.
Zhao, Fang, et al.. (2021). Sarco/endoplasmic reticulum Ca2+‐ATPase (SERCA2b) mediates oxidation‐induced endoplasmic reticulum stress to regulate neuropathic pain. British Journal of Pharmacology. 179(9). 2016–2036. 22 indexed citations
8.
Ma, Xuefei, Yun Tian, Zhihong Xiao, et al.. (2021). A conserved residue in the P2X4 receptor has a nonconserved function in ATP recognition. Journal of Biological Chemistry. 296. 100655–100655. 4 indexed citations
9.
Li, Wei‐Guang, Yan‐Jiao Wu, Xue Gu, et al.. (2021). Input associativity underlies fear memory renewal. National Science Review. 8(9). nwab004–nwab004. 11 indexed citations
10.
Ma, Lina, Weiji Weng, Yingping Wang, et al.. (2020). DUSP6 SUMOylation protects cells from oxidative damage via direct regulation of Drp1 dephosphorylation. Science Advances. 6(13). 62 indexed citations
11.
Wang, Hongbo, Xiaoding Cheng, Jinbin Tian, et al.. (2020). TRPC channels: Structure, function, regulation and recent advances in small molecular probes. Pharmacology & Therapeutics. 209. 107497–107497. 150 indexed citations
12.
Thakur, Dhananjay, et al.. (2020). Intracellular acidification facilitates receptor‐operated TRPC4 activation through PLCδ1 in a Ca2+‐dependent manner. The Journal of Physiology. 598(13). 2651–2667. 11 indexed citations
13.
Liu, Fan, et al.. (2020). ASIC1a channels regulate mitochondrial ion signaling and energy homeostasis in neurons. Journal of Neurochemistry. 153(2). 203–215. 15 indexed citations
14.
Qi, Xin, Ying Li, Oleksandr Maximyuk, et al.. (2019). Protein Kinase C Lambda Mediates Acid-Sensing Ion Channel 1a-Dependent Cortical Synaptic Plasticity and Pain Hypersensitivity. Journal of Neuroscience. 39(29). 5773–5793. 25 indexed citations
15.
Li, Bin, Jin Wang, Xiaoyang Cheng, et al.. (2018). Molecular mechanism underlying the subtype-selectivity of competitive inhibitor NF110 and its distinct potencies in human and rat P2X3 receptors. Science Bulletin. 63(24). 1616–1625. 12 indexed citations
17.
Xie, Rui, Jingyu Xu, Yufeng Xiao, et al.. (2017). Calcium Promotes Human Gastric Cancer via a Novel Coupling of Calcium-Sensing Receptor and TRPV4 Channel. Cancer Research. 77(23). 6499–6512. 88 indexed citations
18.
Sun, Hao, Yong Zuo, Yan Wang, et al.. (2014). Kainate receptor activation induces glycine receptor endocytosis through PKC deSUMOylation. Nature Communications. 5(1). 4980–4980. 41 indexed citations
19.
Yang, Yang, Ye Yu, Yan Liu, et al.. (2012). Highly Conserved Salt Bridge Stabilizes Rigid Signal Patch at Extracellular Loop Critical for Surface Expression of Acid-sensing Ion Channels. Journal of Biological Chemistry. 287(18). 14443–14455. 17 indexed citations
20.
Kinoshita-Kawada, Mariko, John Oberdick, & Michael X. Zhu. (2004). A Purkinje cell specific GoLoco domain protein, L7/Pcp-2, modulates receptor-mediated inhibition of Cav2.1 Ca2+ channels in a dose-dependent manner. Molecular Brain Research. 132(1). 73–86. 28 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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