Aaron M. Beedle

2.6k total citations
49 papers, 2.0k citations indexed

About

Aaron M. Beedle is a scholar working on Molecular Biology, Cellular and Molecular Neuroscience and Cell Biology. According to data from OpenAlex, Aaron M. Beedle has authored 49 papers receiving a total of 2.0k indexed citations (citations by other indexed papers that have themselves been cited), including 44 papers in Molecular Biology, 17 papers in Cellular and Molecular Neuroscience and 14 papers in Cell Biology. Recurrent topics in Aaron M. Beedle's work include Muscle Physiology and Disorders (16 papers), Ion channel regulation and function (14 papers) and Neuroscience and Neuropharmacology Research (10 papers). Aaron M. Beedle is often cited by papers focused on Muscle Physiology and Disorders (16 papers), Ion channel regulation and function (14 papers) and Neuroscience and Neuropharmacology Research (10 papers). Aaron M. Beedle collaborates with scholars based in United States, Canada and Japan. Aaron M. Beedle's co-authors include Gerald W. Zamponi, Jawed Hamid, Kevin P. Campbell, Clinton J. Doering, John E. McRory, Isabelle Latour, Scott E. Jarvis, Johanna Magga, Jarrod A. Call and Janice E.A. Braun and has published in prestigious journals such as Journal of Biological Chemistry, Journal of Clinical Investigation and Nature Communications.

In The Last Decade

Aaron M. Beedle

48 papers receiving 2.0k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Aaron M. Beedle United States 25 1.5k 873 323 300 171 49 2.0k
Heng Wu China 22 1.4k 0.9× 292 0.3× 173 0.5× 270 0.9× 114 0.7× 43 2.2k
Hideaki Ando Japan 22 1.9k 1.2× 441 0.5× 175 0.5× 288 1.0× 65 0.4× 37 2.6k
Venugopalan D. Nair United States 22 936 0.6× 331 0.4× 220 0.7× 120 0.4× 57 0.3× 51 1.6k
Elke Persohn Switzerland 20 1.3k 0.9× 1.2k 1.4× 288 0.9× 243 0.8× 296 1.7× 37 2.6k
Kambiz N. Alavian United States 25 1.7k 1.1× 543 0.6× 203 0.6× 135 0.5× 66 0.4× 46 2.4k
Kouzin Kamino Japan 26 1.2k 0.8× 289 0.3× 1.0k 3.1× 177 0.6× 81 0.5× 70 2.3k
Xiao-ding Peng United States 25 2.8k 1.8× 588 0.7× 385 1.2× 196 0.7× 104 0.6× 35 3.5k
Andreas Weiss Switzerland 33 2.7k 1.8× 2.2k 2.5× 274 0.8× 366 1.2× 66 0.4× 66 3.6k
Satish Patel United Kingdom 24 2.1k 1.4× 300 0.3× 302 0.9× 273 0.9× 131 0.8× 43 2.8k
Maribel P. Lim United States 11 597 0.4× 444 0.5× 138 0.4× 201 0.7× 31 0.2× 12 1.1k

Countries citing papers authored by Aaron M. Beedle

Since Specialization
Citations

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

Fields of papers citing papers by Aaron M. Beedle

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Aaron M. Beedle. 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 Aaron M. Beedle. The network helps show where Aaron M. Beedle may publish in the future.

Co-authorship network of co-authors of Aaron M. Beedle

This figure shows the co-authorship network connecting the top 25 collaborators of Aaron M. Beedle. A scholar is included among the top collaborators of Aaron M. Beedle 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 Aaron M. Beedle. Aaron M. Beedle 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
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Xie, Liwei, Amelia Yin, Anna S. Nichenko, et al.. (2018). Transient HIF2A inhibition promotes satellite cell proliferation and muscle regeneration. Journal of Clinical Investigation. 128(6). 2339–2355. 50 indexed citations
3.
Yu, Seok‐Ho, Peng Zhao, Pradeep Kumar Prabhakar, et al.. (2018). Defective mucin-type glycosylation on α-dystroglycan in COG-deficient cells increases its susceptibility to bacterial proteases. Journal of Biological Chemistry. 293(37). 14534–14544. 3 indexed citations
4.
Gicquel, Evelyne, William Martin, Nathalie Bourg, et al.. (2017). AAV-mediated transfer of FKRP shows therapeutic efficacy in a murine model but requires control of gene expression. Human Molecular Genetics. 26(10). 1952–1965. 35 indexed citations
5.
Call, Jarrod A., et al.. (2016). Four-week rapamycin treatment improves muscular dystrophy in a fukutin-deficient mouse model of dystroglycanopathy. Skeletal Muscle. 6(1). 20–20. 21 indexed citations
6.
7.
Oruganty, Krishnadev, et al.. (2015). Inhibiting EGFR Dimerization Using Triazolyl-Bridged Dimerization Arm Mimics. PLoS ONE. 10(3). e0118796–e0118796. 30 indexed citations
8.
Nguyen, Há Thi, Wei Jia, Aaron M. Beedle, Eileen J. Kennedy, & Mandi M. Murph. (2015). Lysophosphatidic Acid Mediates Activating Transcription Factor 3 Expression Which Is a Target for Post-Transcriptional Silencing by miR-30c-2-3p. PLoS ONE. 10(9). e0139489–e0139489. 4 indexed citations
9.
Watkins, Christopher, et al.. (2015). Design of a selenylsulfide-bridged EGFR dimerization arm mimic. Bioorganic & Medicinal Chemistry. 23(12). 2761–2766. 9 indexed citations
10.
Altman, Molly K., Ali A. Alshamrani, Wei Jia, et al.. (2015). Suppression of the GTPase-activating protein RGS10 increases Rheb-GTP and mTOR signaling in ovarian cancer cells. Cancer Letters. 369(1). 175–183. 22 indexed citations
11.
Hollinger, Katrin, et al.. (2014). Development of Rabbit Monoclonal Antibodies for Detection of Alpha-Dystroglycan in Normal and Dystrophic Tissue. PLoS ONE. 9(5). e97567–e97567. 12 indexed citations
12.
Beedle, Aaron M., et al.. (2012). Mouse fukutin deletion impairs dystroglycan processing and recapitulates muscular dystrophy. Journal of Clinical Investigation. 122(9). 3330–3342. 49 indexed citations
13.
Kiyonaka, Shigeki, Minoru Wakamori, Takafumi Miki, et al.. (2007). RIM1 confers sustained activity and neurotransmitter vesicle anchoring to presynaptic Ca2+ channels. Nature Neuroscience. 10(6). 691–701. 185 indexed citations
14.
McRory, John E., Jawed Hamid, Clinton J. Doering, et al.. (2004). The CACNA1F Gene Encodes an L-Type Calcium Channel with Unique Biophysical Properties and Tissue Distribution. Journal of Neuroscience. 24(7). 1707–1718. 154 indexed citations
15.
Beedle, Aaron M., John E. McRory, Olivier Poirot, et al.. (2004). Agonist-independent modulation of N-type calcium channels by ORL1 receptors. Nature Neuroscience. 7(2). 118–125. 114 indexed citations
16.
Beedle, Aaron M., Jawed Hamid, & Gerald W. Zamponi. (2002). . The Journal of Membrane Biology. 187(3). 225–238. 77 indexed citations
17.
Kumar, P. Phani, Stephanie C. Stotz, R. Paramashivappa, et al.. (2002). Synthesis and Evaluation of a New Class of Nifedipine Analogs with T-Type Calcium Channel Blocking Activity. Molecular Pharmacology. 61(3). 649–658. 69 indexed citations
18.
Beedle, Aaron M. & Gerald W. Zamponi. (2000). Block of Voltage-Dependent Calcium Channels by Aliphatic Monoamines. Biophysical Journal. 79(1). 260–270. 15 indexed citations
19.
Jarvis, Scott E., Johanna Magga, Aaron M. Beedle, Janice E.A. Braun, & Gerald W. Zamponi. (2000). G Protein Modulation of N-type Calcium Channels Is Facilitated by Physical Interactions between Syntaxin 1A and Gβγ. Journal of Biological Chemistry. 275(9). 6388–6394. 111 indexed citations
20.
Washburn, David L.S., Aaron M. Beedle, & Alastair V. Ferguson. (1999). Inhibition of subfornical organ neuronal potassium channels by vasopressin. Neuroscience. 93(1). 349–359. 26 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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