William Duddy
Impact in
Papers in
-
- Muscle Physiology and Disorders 24
- RNA Research and Splicing 6
- Bioinformatics and Genomic Networks 5
- CRISPR and Genetic Engineering 4
- Extracellular vesicles in disease 4
- Neurology 14
- Amyotrophic Lateral Sclerosis Research 14
- Neurological diseases and metabolism 4
- Co-authors
- Stéphanie Duguez (27 shared papers)Toshifumi Yokota (11 shared papers)Laura Le Gall (6 shared papers)Terence A. Partridge (6 shared papers)Vincent Mouly (6 shared papers)Yusuke Echigoya (6 shared papers)Gillian Butler‐Browne (6 shared papers)E. James Milner‐White (2 shared papers)
- Journals
- Journal of Personalized Medicine (7 papers)Skeletal Muscle (4 papers)Cells (3 papers)PLoS ONE (3 papers)Molecular Therapy (2 papers)
- Partner nations
- United KingdomFranceUnited States
In The Last Decade
William Duddy
45 papers receiving 1.3k citations
Peers
Comparison fields: 5 of 88
- Genetics 305
- Aging 32
- Neurology 274
- Molecular Biology 1.1k
- Physiology 213
Countries citing papers authored by William Duddy
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
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-authors
The 25 scholars most cited alongside William Duddy, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 45 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2015 | 99 | |
| 2 | 2020 | 94 | |
| 3 | 2015 | 82 | |
| 4 | 2020 | 72 | |
| 5 | 2004 | 63 | |
| 6 | 2017 | 62 | |
| 7 | 2016 | 60 | |
| 8 | Optimizing exon skipping therapies for DMD. | 2007 | 57 |
| 9 | 2019 | 55 | |
| 10 | 2015 | 51 | |
| 11 | 2017 | 49 | |
| 12 | 2013 | 48 | |
| 13 | 2012 | 44 | |
| 14 | 2007 | 40 | |
| 15 | 2021 | 36 | |
| 16 | 2020 | 34 | |
| 17 | 2019 | 32 | |
| 18 | 2021 | 32 | |
| 19 | 2012 | 31 | |
| 20 | 2018 | 30 |
About William Duddy
William Duddy is a scholar working on Molecular Biology, Neurology, Genetics, Physiology and Genetics, having authored 45 papers that have together received 1.3k indexed citations. Recurring topics across this work include Muscle Physiology and Disorders (24 papers), Amyotrophic Lateral Sclerosis Research (14 papers), Neurogenetic and Muscular Disorders Research (12 papers), RNA Research and Splicing (6 papers), Bioinformatics and Genomic Networks (5 papers), CRISPR and Genetic Engineering (4 papers), Neurological diseases and metabolism (4 papers) and Extracellular vesicles in disease (4 papers). The work is most often cited by research in Genetics (305 citations), Aging (32 citations), Neurology (274 citations), Molecular Biology (1.1k citations) and Physiology (213 citations). William Duddy has collaborated with scholars based in United Kingdom, France and United States. Frequent co-authors include Stéphanie Duguez, Toshifumi Yokota, Laura Le Gall, Terence A. Partridge, Vincent Mouly, Yusuke Echigoya, Gillian Butler‐Browne, E. James Milner‐White, Frank H. Allen and J. Willem M. Nissink. Their work appears in journals such as Journal of Personalized Medicine, Skeletal Muscle, Cells, PLoS ONE and Molecular Therapy.
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.