William Duddy

1.9k total citations
45 papers, 1.3k citations indexed

About

William Duddy is a scholar working on Molecular Biology, Neurology and Genetics. According to data from OpenAlex, William Duddy has authored 45 papers receiving a total of 1.3k indexed citations (citations by other indexed papers that have themselves been cited), including 37 papers in Molecular Biology, 14 papers in Neurology and 13 papers in Genetics. Recurrent topics in William Duddy's work include Muscle Physiology and Disorders (24 papers), Amyotrophic Lateral Sclerosis Research (14 papers) and Neurogenetic and Muscular Disorders Research (12 papers). William Duddy is often cited by papers focused on Muscle Physiology and Disorders (24 papers), Amyotrophic Lateral Sclerosis Research (14 papers) and Neurogenetic and Muscular Disorders Research (12 papers). William Duddy collaborates with scholars based in United Kingdom, France and United States. William Duddy's co-authors include Stéphanie Duguez, Toshifumi Yokota, Laura Le Gall, Terence A. Partridge, Vincent Mouly, Yusuke Echigoya, Gillian Butler‐Browne, E. James Milner‐White, J. Willem M. Nissink and Frank H. Allen and has published in prestigious journals such as Nucleic Acids Research, PLoS ONE and International Journal of Molecular Sciences.

In The Last Decade

William Duddy

45 papers receiving 1.3k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
William Duddy United Kingdom 21 1.1k 305 274 213 125 45 1.3k
Marco Baralle Italy 20 1.4k 1.3× 512 1.7× 795 2.9× 182 0.9× 136 1.1× 46 1.9k
Valentina Sardone United Kingdom 13 850 0.8× 439 1.4× 552 2.0× 126 0.6× 100 0.8× 14 1.2k
Carlo Rinaldi Italy 21 1.2k 1.1× 345 1.1× 306 1.1× 93 0.4× 148 1.2× 47 1.7k
Sandra R. Bacman United States 24 1.8k 1.6× 101 0.3× 214 0.8× 542 2.5× 208 1.7× 49 2.5k
Helen Griffin United Kingdom 23 1.0k 1.0× 117 0.4× 174 0.6× 92 0.4× 247 2.0× 49 1.5k
Jens Reimann Germany 22 845 0.8× 171 0.6× 192 0.7× 176 0.8× 58 0.5× 55 1.3k
Marc‐David Ruepp Switzerland 21 1.7k 1.5× 380 1.2× 377 1.4× 61 0.3× 54 0.4× 48 1.9k
Owen A. Brady United States 13 700 0.6× 206 0.7× 666 2.4× 518 2.4× 57 0.5× 14 1.7k
Alexander Reuter Germany 17 670 0.6× 85 0.3× 197 0.7× 130 0.6× 91 0.7× 25 1.3k

Countries citing papers authored by William Duddy

Since Specialization
Citations

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

Fields of papers citing papers by William Duddy

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of William Duddy

This figure shows the co-authorship network connecting the top 25 collaborators of William Duddy. A scholar is included among the top collaborators of William Duddy 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 William Duddy. William Duddy 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.
McCluskey, Gavin, Karen Morrison, Colette Donaghy, et al.. (2023). Serum Neurofilaments in Motor Neuron Disease and Their Utility in Differentiating ALS, PMA and PLS. Life. 13(6). 1301–1301. 7 indexed citations
2.
McCluskey, Gavin, et al.. (2023). Genome-Wide Gene-Set Analysis Identifies Molecular Mechanisms Associated with ALS. International Journal of Molecular Sciences. 24(4). 4021–4021. 1 indexed citations
3.
Malatras, Apostolos, Konstantinos Kyriakidis, Stéphanie Duguez, et al.. (2023). HGCA2.0: An RNA-Seq Based Webtool for Gene Coexpression Analysis in Homo sapiens. Cells. 12(3). 388–388. 4 indexed citations
4.
McCluskey, Gavin, Karen Morrison, Colette Donaghy, et al.. (2022). Extracellular Vesicles in Amyotrophic Lateral Sclerosis. Life. 13(1). 121–121. 20 indexed citations
5.
McCluskey, Gavin, Colette Donaghy, Karen Morrison, et al.. (2022). The Role of Sphingomyelin and Ceramide in Motor Neuron Diseases. Journal of Personalized Medicine. 12(9). 1418–1418. 18 indexed citations
6.
Saxami, Georgia, Apostolos Malatras, Chih‐Hung Jen, et al.. (2021). Arabidopsis Coexpression Tool: a tool for gene coexpression analysis in Arabidopsis thaliana. iScience. 24(8). 102848–102848. 17 indexed citations
7.
McCluskey, Gavin, et al.. (2021). Epidemiology and survival trends of motor neurone disease in Northern Ireland from 2015 to 2019. European Journal of Neurology. 29(3). 707–714. 11 indexed citations
8.
9.
Morris, Andrew P., et al.. (2020). What Can Machine Learning Approaches in Genomics Tell Us about the Molecular Basis of Amyotrophic Lateral Sclerosis?. Journal of Personalized Medicine. 10(4). 247–247. 11 indexed citations
10.
Gall, Laura Le, et al.. (2020). A Systematic Review of Genotype–Phenotype Correlation across Cohorts Having Causal Mutations of Different Genes in ALS. Journal of Personalized Medicine. 10(3). 58–58. 34 indexed citations
11.
Malatras, Apostolos, Ioannis Michalopoulos, Stéphanie Duguez, et al.. (2020). MyoMiner: explore gene co-expression in normal and pathological muscle. BMC Medical Genomics. 13(1). 67–67. 5 indexed citations
12.
Malatras, Apostolos, Stéphanie Duguez, & William Duddy. (2019). Muscle Gene Sets: a versatile methodological aid to functional genomics in the neuromuscular field. Skeletal Muscle. 9(1). 10–10. 7 indexed citations
13.
14.
Maruyama, Rika, et al.. (2018). Identification of Novel Antisense-Mediated Exon Skipping Targets in DYSF for Therapeutic Treatment of Dysferlinopathy. Molecular Therapy — Nucleic Acids. 13. 596–604. 30 indexed citations
15.
Malatras, Apostolos, William Duddy, Laura Le Gall, et al.. (2015). Changes in Communication between Muscle Stem Cells and their Environment with Aging. Journal of Neuromuscular Diseases. 2(3). 205–217. 17 indexed citations
16.
Bigot, Anne, William Duddy, Zamalou Gisèle Ouandaogo, et al.. (2015). Age-Associated Methylation Suppresses SPRY1, Leading to a Failure of Re-quiescence and Loss of the Reserve Stem Cell Pool in Elderly Muscle. Cell Reports. 13(6). 1172–1182. 82 indexed citations
17.
Duddy, William, Tatiana V. Cohen, Stéphanie Duguez, & Terence A. Partridge. (2011). The isolated muscle fibre as a model of disuse atrophy: Characterization using PhAct, a method to quantify f-actin. Experimental Cell Research. 317(14). 1979–1993. 13 indexed citations
18.
Yokota, Toshifumi, et al.. (2007). Potential of oligonucleotide-mediated exon-skipping therapy for Duchenne muscular dystrophy. Expert Opinion on Biological Therapy. 7(6). 831–842. 40 indexed citations
19.
Milner‐White, E. James, J. Willem M. Nissink, Frank H. Allen, & William Duddy. (2004). Recurring main-chain anion-binding motifs in short polypeptides: nests. Acta Crystallographica Section D Biological Crystallography. 60(11). 1935–1942. 29 indexed citations
20.
Duddy, William, J. Willem M. Nissink, Frank H. Allen, & E. James Milner‐White. (2004). Mimicry by asx‐ and ST‐turns of the four main types of β‐turn in proteins. Protein Science. 13(11). 3051–3055. 63 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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