James M. Ervasti
- Molecular Biology top 0.5%
- Cell Biology top 0.2%
- Physiology top 1%
- Cardiology and Cardiovascular Medicine top 1%
- Cellular and Molecular Neuroscience top 1%
- Co-authors
- Kevin P. CampbellKay OhlendieckSteven D. KahlInna N. RybakovaBenjamin J. PerrinSuzanne W. SernettClive A. SlaughterOxana Ibraghimov‐Beskrovnaya
- Topics
- Muscle Physiology and Disorders (90 papers)Exercise and Physiological Responses (30 papers)Cardiomyopathy and Myosin Studies (27 papers)
- Partner nations
- United StatesFranceAustralia
In The Last Decade
James M. Ervasti
116 papers receiving 10.0k citations
Hit Papers
Peers
Comparison fields: 5 of 129
- Molecular Biology 8.7k
- Cell Biology 2.5k
- Physiology 2.0k
- Cardiology and Cardiovascular Medicine 2.0k
- Cellular and Molecular Neuroscience 1.8k
Countries citing papers authored by James M. Ervasti
This map shows the geographic impact of James M. Ervasti'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 James M. Ervasti with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites James M. Ervasti more than expected).
Fields of papers citing papers by James M. Ervasti
This network shows the impact of papers produced by James M. Ervasti. 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 James M. Ervasti. The network helps show where James M. Ervasti may publish in the future.
Co-authorship network of co-authors of James M. Ervasti
This figure shows the co-authorship network connecting the top 25 collaborators of James M. Ervasti. A scholar is included among the top collaborators of James M. Ervasti 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 James M. Ervasti. James M. Ervasti is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 8 | |
| 2 | 25 | |
| 3 | 30 | |
| 4 | 24 | |
| 5 | 26 | |
| 6 | 35 | |
| 7 | 174 | |
| 8 | 32 | |
| 9 | 15 | |
| 10 | 77 | |
| 11 | 153 | |
| 12 | 241 | |
| 13 | 333 | |
| 14 | 84 | |
| 15 | Dystrophin and utrophin are functionally homologous actin binding proteins but act through distinct modes of filament association | 1 |
| 16 | 55 | |
| 17 | 12 | |
| 18 | 60 | |
| 19 | Membrane organization of the dystrophin-glycoprotein complexbreakdown → | 1107 |
| 20 | 6 |
About James M. Ervasti
James M. Ervasti is a scholar working on Rehabilitation, Cell Biology and Molecular Biology, having authored 117 papers that have together received 10.2k indexed citations. Recurring topics across this work include Muscle Physiology and Disorders (90 papers), Exercise and Physiological Responses (30 papers) and Cardiomyopathy and Myosin Studies (27 papers). The work is most often cited by research in Rehabilitation (1.4k citations), Cell Biology (2.5k citations) and Molecular Biology (8.7k citations). James M. Ervasti has collaborated with scholars based in United States, France and Australia. Frequent co-authors include Kevin P. Campbell, Kay Ohlendieck, Steven D. Kahl, Inna N. Rybakova, Benjamin J. Perrin, Suzanne W. Sernett, Clive A. Slaughter, Oxana Ibraghimov‐Beskrovnaya, Kiichiro Matsumura and Kevin J. Sonnemann. Their work appears in journals such as Nature, Cell and Proceedings of the National Academy of Sciences.
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.