David Beeson

8.4k total citations · 1 hit paper
135 papers, 5.1k citations indexed

About

David Beeson is a scholar working on Neurology, Molecular Biology and Cell Biology. According to data from OpenAlex, David Beeson has authored 135 papers receiving a total of 5.1k indexed citations (citations by other indexed papers that have themselves been cited), including 94 papers in Neurology, 65 papers in Molecular Biology and 27 papers in Cell Biology. Recurrent topics in David Beeson's work include Myasthenia Gravis and Thymoma (88 papers), Ion channel regulation and function (37 papers) and Cellular transport and secretion (24 papers). David Beeson is often cited by papers focused on Myasthenia Gravis and Thymoma (88 papers), Ion channel regulation and function (37 papers) and Cellular transport and secretion (24 papers). David Beeson collaborates with scholars based in United Kingdom, United States and India. David Beeson's co-authors include Angela Vincent, John Newsom–Davis, Jacqueline Palace, Susan Maxwell, Judith Cossins, Pedro M. Rodríguez Cruz, Patrick Waters, Bethan Lang, M Brydson and Sarosh R. Irani and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Nucleic Acids Research and Journal of Biological Chemistry.

In The Last Decade

David Beeson

131 papers receiving 5.0k citations

Hit Papers

N-methyl-d-aspartate anti... 2010 2026 2015 2020 2010 250 500 750

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author Last Decade Papers Cites
David Beeson 3.4k 1.9k 797 625 547 135 5.1k
David Beeson 2.5k 0.7× 1.1k 0.6× 545 0.7× 308 0.5× 229 0.4× 79 3.7k
Eduard Gallardo 1.7k 0.5× 2.2k 1.2× 435 0.5× 1.1k 1.8× 164 0.3× 133 4.6k
Bruno Giometto 3.5k 1.0× 827 0.4× 181 0.2× 1.2k 1.9× 576 1.1× 122 5.3k
Osamu Higuchi 999 0.3× 2.0k 1.1× 1.1k 1.3× 536 0.9× 195 0.4× 86 4.3k
Erdem Tüzün 4.6k 1.3× 1.1k 0.6× 241 0.3× 809 1.3× 1.1k 2.0× 248 6.4k
Véronique Rogemond 3.4k 1.0× 1.3k 0.7× 659 0.8× 1.8k 2.8× 860 1.6× 112 5.4k
Wim Robberecht 1.2k 0.3× 1.5k 0.8× 252 0.3× 1.1k 1.8× 420 0.8× 73 3.8k
Susan Maxwell 1.9k 0.5× 770 0.4× 431 0.5× 274 0.4× 387 0.7× 39 2.4k
Luís Bataller 4.8k 1.4× 1.1k 0.6× 462 0.6× 1.4k 2.3× 1.1k 2.1× 64 5.6k
Shin J. Oh 2.7k 0.8× 1.4k 0.7× 639 0.8× 1.2k 1.9× 151 0.3× 128 5.4k

Countries citing papers authored by David Beeson

Since Specialization
Citations

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

Fields of papers citing papers by David Beeson

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of David Beeson

This figure shows the co-authorship network connecting the top 25 collaborators of David Beeson. A scholar is included among the top collaborators of David Beeson 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 David Beeson. David Beeson 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.
Li, Anna, A.C.W. Pike, Richard Webster, et al.. (2025). Structures of the human adult muscle-type nicotinic receptor in resting and desensitized states. Cell Reports. 44(5). 115581–115581.
2.
Dong, Yin Yao, et al.. (2025). Myasthenic syndromes: mistaking genetic for acquired. Practical Neurology. 26(2). 164–168.
3.
Cossins, Judith, et al.. (2024). Dose escalation pre-clinical trial of novel DOK7-AAV in mouse model of DOK7 congenital myasthenia. Brain Communications. 7(1). fcaf046–fcaf046. 1 indexed citations
4.
Rea, Edward, Julia S. Scott, Susan Maxwell, et al.. (2024). Unraveling the molecular interactions between α7 nicotinic receptor and a RIC3 variant associated with backward speech. Cellular and Molecular Life Sciences. 81(1). 129–129. 3 indexed citations
5.
Everett, Ruth, Yan Dong, C. Marini Bettolo, et al.. (2024). 498P Neuromuscular centre effect on prevalence of congenital myasthenic syndrome (CMS) in the UK. Neuromuscular Disorders. 43. 104441.631–104441.631.
6.
Ramdas, Sithara, et al.. (2024). Assessing the Utility of ColabFold and AlphaMissense in Determining Missense Variant Pathogenicity for Congenital Myasthenic Syndromes. Biomedicines. 12(11). 2549–2549. 2 indexed citations
7.
Dong, Yuan, et al.. (2024). 240P Late presentation DOK7 congenital myasthenia syndrome (CMS), misdiagnosed as myasthenia gravis (MG)– a case series. Neuromuscular Disorders. 43. 104441.623–104441.623.
8.
Samuels, Martin, Jacqueline Palace, David Beeson, et al.. (2023). Congenital myasthenic syndromes: a retrospective natural history study of respiratory outcomes in a single centre. Brain Communications. 5(6). fcad299–fcad299. 5 indexed citations
9.
Cao, Michelangelo, Wei Wei Liu, Susan Maxwell, et al.. (2023). IgG1-3 MuSK Antibodies Inhibit AChR Cluster Formation, Restored by SHP2 Inhibitor, Despite Normal MuSK, DOK7, or AChR Subunit Phosphorylation. Neurology Neuroimmunology & Neuroinflammation. 10(6). 6 indexed citations
10.
Spendiff, Sally, Yin Yao Dong, Lorenzo Maggi, et al.. (2022). 260th ENMC International Workshop: Congenital myasthenic syndromes 11-13 March 2022, Hoofddorp, The Netherlands. Neuromuscular Disorders. 33(9). 111–118. 5 indexed citations
11.
Cossins, Judith, Richard Webster, Susan Maxwell, et al.. (2020). Congenital myasthenic syndrome due to a TOR1AIP1 mutation: a new disease pathway for impaired synaptic transmission. Brain Communications. 2(2). fcaa174–fcaa174. 14 indexed citations
12.
Cossins, Judith, et al.. (2018). Beta-2 Adrenergic Receptor Agonists Enhance AChR Clustering in C2C12 Myotubes: Implications for Therapy of Myasthenic Disorders. Journal of Neuromuscular Diseases. 5(2). 231–240. 36 indexed citations
13.
Finlayson, Sarah, Masliza Mahmod, Theodoros D. Karamitsos, et al.. (2014). A novel cardiac phenotype in patients with GFPT1 or DPAGT1 mutations. 20(8). 3139–3145. 1 indexed citations
14.
Burke, Georgina, Andrea Klein, E. Niks, et al.. (2012). Salbutamol benefits children with congenital myasthenic syndrome due to DOK7 mutations. Neuromuscular Disorders. 23(2). 170–175. 57 indexed citations
15.
Salih, Mustafa A., Darren T. Oystreck, Yasser H. Al‐Faky, et al.. (2010). Congenital Myasthenic Syndrome Due to Homozygous CHRNE Mutations: Report of Patients in Arabia. Journal of Neuro-Ophthalmology. 31(1). 42–47. 15 indexed citations
16.
Waters, Patrick, Sven Jarius, Edward Littleton, et al.. (2007). A novel sensitive assay for aqueporin-4 antibodies (NMO-IgG). Journal of Neurology Neurosurgery & Psychiatry. 78. 1030–1030. 1 indexed citations
17.
Leite, Maria Isabel, Judith Cossins, David Beeson, Nick Willcox, & Angela Vincent. (2006). Antibodies to AChRs in seronegative myasthenia gravis. Journal of Neuroimmunology. 178. 123–123. 1 indexed citations
18.
McConville, J., Willis S. Hoch, David Beeson, John Newsom–Davis, & Angela Vincent. (2002). Detection of musk antibodies in seronegative myasthenia gravis using human musk as antigen. Journal of Neurology Neurosurgery & Psychiatry. 73. 222–222. 3 indexed citations
19.
Beeson, David. (2000). Social and ethical challenges of prenatal diagnosis.. PubMed. 1–2, 8. 1 indexed citations
20.
Beeson, David, M Brydson, & John Newsom–Davis. (1989). Nucleotide sequence of human muscle acetylcholine receptor β-subunit. Nucleic Acids Research. 17(11). 4391–4391. 34 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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