Simone Spuler

5.7k total citations
104 papers, 3.3k citations indexed

About

Simone Spuler is a scholar working on Molecular Biology, Neurology and Surgery. According to data from OpenAlex, Simone Spuler has authored 104 papers receiving a total of 3.3k indexed citations (citations by other indexed papers that have themselves been cited), including 75 papers in Molecular Biology, 15 papers in Neurology and 14 papers in Surgery. Recurrent topics in Simone Spuler's work include Muscle Physiology and Disorders (50 papers), RNA Research and Splicing (14 papers) and Cardiomyopathy and Myosin Studies (11 papers). Simone Spuler is often cited by papers focused on Muscle Physiology and Disorders (50 papers), RNA Research and Splicing (14 papers) and Cardiomyopathy and Myosin Studies (11 papers). Simone Spuler collaborates with scholars based in Germany, United States and France. Simone Spuler's co-authors include Andrew G. Engel, Carmen Birchmeier, Steffen Weber‐Carstens, Claudia Spies, Andreas Marg, Joachim Spranger, Raymond Voltz, Susanne Koch, Tarek Yousry and Maria Deja and has published in prestigious journals such as Circulation, Journal of Clinical Investigation and Nature Medicine.

In The Last Decade

Simone Spuler

99 papers receiving 3.2k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Simone Spuler Germany 34 2.0k 444 444 404 379 104 3.3k
Craig M. Zaidman United States 31 1.0k 0.5× 251 0.6× 406 0.9× 109 0.3× 741 2.0× 82 2.9k
Kenton L. Anderson United States 18 1.1k 0.6× 83 0.2× 289 0.7× 243 0.6× 943 2.5× 45 3.3k
Donald L. Schotland United States 29 1.9k 0.9× 189 0.4× 350 0.8× 99 0.2× 390 1.0× 62 2.8k
Aldobrando Broccolini Italy 26 1.1k 0.5× 273 0.6× 194 0.4× 80 0.2× 301 0.8× 84 1.9k
Aad Verrips Netherlands 27 1.1k 0.6× 150 0.3× 448 1.0× 52 0.1× 549 1.4× 90 3.1k
Florian P. Limbourg Germany 23 1.5k 0.8× 298 0.7× 316 0.7× 43 0.1× 131 0.3× 56 2.9k
Marcello Villanova Italy 27 1.3k 0.6× 223 0.5× 274 0.6× 40 0.1× 289 0.8× 86 2.3k
Angelika F. Hahn Canada 35 985 0.5× 362 0.8× 403 0.9× 689 1.7× 2.6k 6.9× 48 4.2k
Rongcai Jiang China 32 1.6k 0.8× 113 0.3× 145 0.3× 132 0.3× 1.4k 3.8× 143 3.5k
Moris J. Danon United States 16 411 0.2× 224 0.5× 233 0.5× 142 0.4× 439 1.2× 32 1.5k

Countries citing papers authored by Simone Spuler

Since Specialization
Citations

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

Fields of papers citing papers by Simone Spuler

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Simone Spuler

This figure shows the co-authorship network connecting the top 25 collaborators of Simone Spuler. A scholar is included among the top collaborators of Simone Spuler 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 Simone Spuler. Simone Spuler 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.
Graf, Robin, Andreas Marg, Mina Petkova, et al.. (2025). Gene-editing in patient and humanized-mice primary muscle stem cells rescues dysferlin expression in dysferlin-deficient muscular dystrophy. Nature Communications. 16(1). 120–120. 1 indexed citations
2.
Spuler, Simone, Gian Domenico Borasio, & Ulrike Grittner. (2024). Lessons from a negative gene therapy trial for Duchenne muscular dystrophy. Nature Medicine. 31(1). 37–38. 2 indexed citations
3.
Gerhalter, Teresa, Christina Müller, Anja Mähler, et al.. (2023). “suMus,” a novel digital system for arm movement metrics and muscle energy expenditure. Frontiers in Physiology. 14. 1057592–1057592. 2 indexed citations
4.
Marg, Andreas, et al.. (2022). mRNA-mediated delivery of gene editing tools to human primary muscle stem cells. Molecular Therapy — Nucleic Acids. 28. 47–57. 22 indexed citations
5.
Boyer, Olivier, Gillian Butler‐Browne, Hector Chinoy, et al.. (2021). Myogenic Cell Transplantation in Genetic and Acquired Diseases of Skeletal Muscle. Frontiers in Genetics. 12. 702547–702547. 20 indexed citations
6.
Lahmann, Ines, Dominique Bröhl, Akihiro Isomura, et al.. (2019). Oscillations of MyoD and Hes1 proteins regulate the maintenance of activated muscle stem cells. Genes & Development. 33(9-10). 524–535. 62 indexed citations
7.
Moore, U., M. James, Marni Jacobs, et al.. (2019). P.188The clinical outcome study for dysferlinopathy: pregnancy in dysferlinopathy. Neuromuscular Disorders. 29. S104–S104. 1 indexed citations
8.
Bhattarai, Salyan, Sabine Krause, Olivier Benvéniste, et al.. (2016). The immunoproteasomes are key to regulate myokines and MHC class I expression in idiopathic inflammatory myopathies. Journal of Autoimmunity. 75. 118–129. 34 indexed citations
10.
Keller, Sarah, Séverine Kunz, Michael Boschmann, et al.. (2015). The Metabolic Footprint of Dysferlinopathy (P2.048). Neurology. 84(14_supplement). 1 indexed citations
11.
Wollersheim, Tobias, Martin Krebs, Kurt Haas, et al.. (2014). Dynamics of myosin degradation in intensive care unit-acquired weakness during severe critical illness. Intensive Care Medicine. 40(4). 528–538. 97 indexed citations
12.
Grounds, Miranda D., Jessica R. Terrill, Hannah G. Radley‐Crabb, et al.. (2014). Lipid Accumulation in Dysferlin-Deficient Muscles. American Journal Of Pathology. 184(6). 1668–1676. 69 indexed citations
13.
Weber‐Carstens, Steffen, Joanna Schneider, Tobias Wollersheim, et al.. (2012). Critical Illness Myopathy and GLUT4. American Journal of Respiratory and Critical Care Medicine. 187(4). 387–396. 83 indexed citations
14.
Zacharias, Ute, et al.. (2011). Ahnak1 abnormally localizes in muscular dystrophies and contributes to muscle vesicle release. Journal of Muscle Research and Cell Motility. 32(4-5). 271–280. 24 indexed citations
15.
Bierbrauer, Jeffrey, Susanne Koch, Joanna Schneider, et al.. (2011). Early type II fiber atrophy in intensive care unit patients with nonexcitable muscle membrane. Critical Care Medicine. 40(2). 647–650. 59 indexed citations
16.
Rajab, Anna, Volker Straub, Liza McCann, et al.. (2010). Fatal Cardiac Arrhythmia and Long-QT Syndrome in a New Form of Congenital Generalized Lipodystrophy with Muscle Rippling (CGL4) Due to PTRF-CAVIN Mutations. PLoS Genetics. 6(3). e1000874–e1000874. 181 indexed citations
17.
Weber‐Carstens, Steffen, Susanne Koch, Simone Spuler, et al.. (2009). Nonexcitable muscle membrane predicts intensive care unit-acquired paresis in mechanically ventilated, sedated patients*. Critical Care Medicine. 37(9). 2632–2637. 62 indexed citations
18.
Röcken, Christoph, Jochen Ernst, Ernst Hund, et al.. (2006). Interdisziplinäre Leitlinien zur Diagnostik und Therapie der extrazerebralen Amyloidosen: Herausgegeben von der Deutschen Gesellschaft für Amyloid-Krankheiten e. V. (www.amyloid.de). Medizinische Klinik - Intensivmedizin und Notfallmedizin. 101(10). 825–829.
19.
Wenzel, Katrin, Claire L. Harris, Mengfatt Ho, et al.. (2005). Increased Susceptibility to Complement Attack due to Down-Regulation of Decay-Accelerating Factor/CD55 in Dysferlin-Deficient Muscular Dystrophy. The Journal of Immunology. 175(9). 6219–6225. 57 indexed citations
20.
Engel, Andrew G., et al.. (2004). Differenzialdiagnostik eines kongenitalen myasthenen Syndroms. Der Nervenarzt. 75(2). 141–144.

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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