Andrew A. Voss

877 total citations
32 papers, 677 citations indexed

About

Andrew A. Voss is a scholar working on Molecular Biology, Cellular and Molecular Neuroscience and Cardiology and Cardiovascular Medicine. According to data from OpenAlex, Andrew A. Voss has authored 32 papers receiving a total of 677 indexed citations (citations by other indexed papers that have themselves been cited), including 29 papers in Molecular Biology, 18 papers in Cellular and Molecular Neuroscience and 13 papers in Cardiology and Cardiovascular Medicine. Recurrent topics in Andrew A. Voss's work include Ion channel regulation and function (17 papers), Genetic Neurodegenerative Diseases (11 papers) and Cardiac electrophysiology and arrhythmias (9 papers). Andrew A. Voss is often cited by papers focused on Ion channel regulation and function (17 papers), Genetic Neurodegenerative Diseases (11 papers) and Cardiac electrophysiology and arrhythmias (9 papers). Andrew A. Voss collaborates with scholars based in United States, Austria and Italy. Andrew A. Voss's co-authors include Donald D. F. Loo, Bruce A. Hirayama, Ernest M. Wright, Charles S. Hummel, Chuan Lü, Isaac N. Pessah, Mark M. Rich, Robert J. Talmadge, Michael A. Ernst‐Russell and Dexter Morin and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Journal of Biological Chemistry and Journal of Neuroscience.

In The Last Decade

Andrew A. Voss

30 papers receiving 668 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Andrew A. Voss United States 14 500 219 177 149 136 32 677
Jeyaganesh Rajamanickam Germany 12 503 1.0× 183 0.8× 125 0.7× 61 0.4× 90 0.7× 12 678
Riad Efendiev United States 20 978 2.0× 118 0.5× 158 0.9× 171 1.1× 140 1.0× 22 1.2k
A. M. Bertorello Sweden 8 637 1.3× 114 0.5× 113 0.6× 85 0.6× 77 0.6× 10 782
Wentong Long Canada 10 290 0.6× 77 0.4× 117 0.7× 80 0.5× 84 0.6× 17 551
Yasushi Sakai Japan 14 236 0.5× 155 0.7× 58 0.3× 56 0.4× 63 0.5× 51 571
Hisanori Hazama Japan 15 330 0.7× 119 0.5× 92 0.5× 241 1.6× 43 0.3× 23 637
Christina Schwanstecher Germany 21 556 1.1× 176 0.8× 324 1.8× 152 1.0× 510 3.8× 28 1.1k
K. W. Snowdowne United States 16 503 1.0× 220 1.0× 49 0.3× 73 0.5× 69 0.5× 22 732
Toshie Kambe Japan 17 373 0.7× 131 0.6× 121 0.7× 281 1.9× 32 0.2× 29 784
Y Ihara Japan 8 368 0.7× 104 0.5× 255 1.4× 24 0.2× 271 2.0× 9 878

Countries citing papers authored by Andrew A. Voss

Since Specialization
Citations

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

Fields of papers citing papers by Andrew A. Voss

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Andrew A. Voss. 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 Andrew A. Voss. The network helps show where Andrew A. Voss may publish in the future.

Co-authorship network of co-authors of Andrew A. Voss

This figure shows the co-authorship network connecting the top 25 collaborators of Andrew A. Voss. A scholar is included among the top collaborators of Andrew A. Voss 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 Andrew A. Voss. Andrew A. Voss 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.
Dupont, Christopher L., et al.. (2025). Discovery and Treatment of Action Potential‐Independent Myotonia in Hyperkalemic Periodic Paralysis. Annals of Clinical and Translational Neurology. 12(10). 2056–2067.
2.
Burke, Steve, et al.. (2024). Exploring lipin1 as a promising therapeutic target for the treatment of Duchenne muscular dystrophy. Journal of Translational Medicine. 22(1). 664–664. 1 indexed citations
3.
Dupont, Christopher L., et al.. (2024). BK channels promote action potential repolarization in skeletal muscle but contribute little to myotonia. Pflügers Archiv - European Journal of Physiology. 476(11). 1693–1702. 1 indexed citations
4.
Nemetchek, Michelle D., et al.. (2024). Agonists of the Nuclear Receptor PPARγ Can Produce Biased Signaling. Molecular Pharmacology. 106(6). 309–318. 1 indexed citations
5.
6.
Burke, Steve, et al.. (2023). Lipin1 plays complementary roles in myofibre stability and regeneration in dystrophic muscles. The Journal of Physiology. 601(5). 961–978. 6 indexed citations
7.
Wang, Xueyong, Christopher L. Dupont, Steve Burke, et al.. (2022). The role of action potential changes in depolarization-induced failure of excitation contraction coupling in mouse skeletal muscle. eLife. 11. 12 indexed citations
8.
Dupont, Christopher L., Ahmed A. Hawash, Andrew G. Koesters, et al.. (2021). The mechanism underlying transient weakness in myotonia congenita. eLife. 10. 13 indexed citations
9.
Rich, Mark M., et al.. (2021). Acetylcholine receptor subunit expression in Huntington's disease mouse muscle. Biochemistry and Biophysics Reports. 28. 101182–101182. 3 indexed citations
10.
Voss, Andrew A., et al.. (2021). Into the spotlight: RGK proteins in skeletal muscle. Cell Calcium. 98. 102439–102439. 2 indexed citations
11.
Romer, Shannon H., Matthew C. Wright, Long‐Sheng Song, et al.. (2021). A mouse model of Huntington’s disease shows altered ultrastructure of transverse tubules in skeletal muscle fibers. The Journal of General Physiology. 153(4). 5 indexed citations
12.
Wang, Xueyong, et al.. (2020). Depressed neuromuscular transmission causes weakness in mice lacking BK potassium channels. The Journal of General Physiology. 152(5). 13 indexed citations
13.
Dupont, Christopher L., et al.. (2019). Treatment of myotonia congenita with retigabine in mice. Experimental Neurology. 315. 52–59. 18 indexed citations
14.
Romer, Shannon H., et al.. (2017). Depressed Synaptic Transmission and Reduced Vesicle Release Sites in Huntington's Disease Neuromuscular Junctions. Journal of Neuroscience. 37(34). 8077–8091. 17 indexed citations
15.
16.
Varuzhanyan, Grigor, et al.. (2013). Huntington disease skeletal muscle is hyperexcitable owing to chloride and potassium channel dysfunction. Proceedings of the National Academy of Sciences. 110(22). 9160–9165. 50 indexed citations
17.
Hummel, Charles S., Chuan Lü, Donald D. F. Loo, et al.. (2010). Glucose transport by human renal Na + / d -glucose cotransporters SGLT1 and SGLT2. American Journal of Physiology-Cell Physiology. 300(1). C14–C21. 218 indexed citations
18.
Voss, Andrew A., Paul D. Allen, Isaac N. Pessah, & Claudio F. Pérez. (2008). Allosterically coupled calcium and magnesium binding sites are unmasked by ryanodine receptor chimeras. Biochemical and Biophysical Research Communications. 366(4). 988–993. 4 indexed citations
19.
Voss, Andrew A., József Langó, Michael A. Ernst‐Russell, Dexter Morin, & Isaac N. Pessah. (2004). Identification of Hyperreactive Cysteines within Ryanodine Receptor Type 1 by Mass Spectrometry. Journal of Biological Chemistry. 279(33). 34514–34520. 68 indexed citations
20.
Pérez, Claudio F., Andrew A. Voss, Isaac N. Pessah, & Paul D. Allen. (2003). RyR1/RyR3 Chimeras Reveal that Multiple Domains of RyR1 Are Involved in Skeletal-Type E-C Coupling. Biophysical Journal. 84(4). 2655–2663. 37 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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