Rita Barresi
Impact in
- Molecular Biology top 2%
- Muscle Physiology and Disorders
- Ion channel regulation and function
- Genetics top 2%
- Mesenchymal stem cell research
- Virus-based gene therapy research
Papers in
-
- Exercise and Physiological Responses 7
-
- Muscle Physiology and Disorders 38
- Nuclear Structure and Function 5
- Co-authors
- Kevin P. CampbellSteven A. MooreDaniel E. MicheleMotoi KanagawaRoger A. WilliamsonMarina MoraLucía MorandiFumiaki Saito
- Journals
- Neuromuscular Disorders (13 papers)Stem Cells and Development (2 papers)Cell (2 papers)Muscle & Nerve (2 papers)Science (2 papers)
- Partner nations
- ItalyUnited StatesUnited Kingdom
In The Last Decade
Rita Barresi
50 papers receiving 3.4k citations
Peers
Comparison fields: 5 of 106
- Molecular Biology 2.8k
- Genetics 424
- Cellular and Molecular Neuroscience 623
- Rehabilitation 226
- Cell Biology 519
Countries citing papers authored by Rita Barresi
This map shows the geographic impact of Rita Barresi'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 Rita Barresi with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Rita Barresi more than expected).
Fields of papers citing papers by Rita Barresi
This network shows the impact of papers produced by Rita Barresi. 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 Rita Barresi. The network helps show where Rita Barresi may publish in the future.
Co-authors
The 25 scholars most cited alongside Rita Barresi, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2024 | 1 | |
| 2 | 2024 | 1 | |
| 3 | 2024 | 1 | |
| 4 | 2024 | 0 | |
| 5 | 2023 | 2 | |
| 6 | 2022 | 10 | |
| 7 | 2020 | 5 | |
| 8 | 2016 | 28 | |
| 9 | 2016 | 26 | |
| 10 | 2015 | 1 | |
| 11 | 2014 | 5 | |
| 12 | 2013 | 7 | |
| 13 | 2013 | 34 | |
| 14 | 2013 | 51 | |
| 15 | 2008 | 62 | |
| 16 | 2004 | 204 | |
| 17 | 2004 | 214 | |
| 18 | 2003 | 212 | |
| 19 | 2000 | 101 | |
| 20 | 1996 | 30 |
About Rita Barresi
Rita Barresi is a scholar working on Rehabilitation, Molecular Biology, Aging, Cell Biology and Cellular and Molecular Neuroscience, having authored 52 papers that have together received 3.5k indexed citations. Recurring topics across this work include Muscle Physiology and Disorders (38 papers), Adipose Tissue and Metabolism (8 papers), Genetic Neurodegenerative Diseases (8 papers), Cardiomyopathy and Myosin Studies (7 papers), Exercise and Physiological Responses (7 papers), Nuclear Structure and Function (5 papers), Mesenchymal stem cell research (3 papers) and Calpain Protease Function and Regulation (3 papers). The work is most often cited by research in Molecular Biology (2.8k citations), Genetics (424 citations), Cellular and Molecular Neuroscience (623 citations), Rehabilitation (226 citations) and Cell Biology (519 citations). Rita Barresi has collaborated with scholars based in Italy, United States and United Kingdom. Frequent co-authors include Kevin P. Campbell, Steven A. Moore, Daniel E. Michele, Motoi Kanagawa, Roger A. Williamson, Marina Mora, Lucía Morandi, Fumiaki Saito, F. Cornelio and Maria Gabriella Cusella De Angelis. Their work appears in journals such as Neuromuscular Disorders, Stem Cells and Development, Cell, Muscle & Nerve and Science.
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.