Gianina Ravenscroft
- Molecular Biology top 10%
- Cardiology and Cardiovascular Medicine top 5%
- Genetics top 2%
- Cellular and Molecular Neuroscience top 5%
- Genetics top 10%
- Co-authors
- Nigel G. LaingKristen L. NowakMark R. DavisSarah J. BeecroftElyshia McNamaraPhillipa J. LamontCarsten G. BönnemannSteven B. Marston
- Topics
- Muscle Physiology and Disorders (43 papers)Cardiomyopathy and Myosin Studies (42 papers)Neurogenetic and Muscular Disorders Research (28 papers)
- Partner nations
- AustraliaUnited KingdomUnited States
In The Last Decade
Gianina Ravenscroft
85 papers receiving 1.5k citations
Peers
Comparison fields: 5 of 93
- Molecular Biology 1.1k
- Cardiology and Cardiovascular Medicine 628
- Genetics 367
- Cellular and Molecular Neuroscience 313
- Genetics 248
Countries citing papers authored by Gianina Ravenscroft
This map shows the geographic impact of Gianina Ravenscroft'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 Gianina Ravenscroft with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Gianina Ravenscroft more than expected).
Fields of papers citing papers by Gianina Ravenscroft
This network shows the impact of papers produced by Gianina Ravenscroft. 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 Gianina Ravenscroft. The network helps show where Gianina Ravenscroft may publish in the future.
Co-authorship network of co-authors of Gianina Ravenscroft
This figure shows the co-authorship network connecting the top 25 collaborators of Gianina Ravenscroft. A scholar is included among the top collaborators of Gianina Ravenscroft 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 Gianina Ravenscroft. Gianina Ravenscroft is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 0 | |
| 3 | 1 | |
| 4 | 4 | |
| 5 | 3 | |
| 6 | 6 | |
| 7 | 0 | |
| 8 | 1 | |
| 9 | 4 | |
| 10 | 8 | |
| 11 | 5 | |
| 12 | 3 | |
| 13 | 7 | |
| 14 | 6 | |
| 15 | 2 | |
| 16 | 6 | |
| 17 | 7 | |
| 18 | 19 | |
| 19 | 8 | |
| 20 | 29 |
About Gianina Ravenscroft
Gianina Ravenscroft is a scholar working on Genetics, Cardiology and Cardiovascular Medicine and Cellular and Molecular Neuroscience, having authored 94 papers that have together received 1.5k indexed citations. Recurring topics across this work include Muscle Physiology and Disorders (43 papers), Cardiomyopathy and Myosin Studies (42 papers) and Neurogenetic and Muscular Disorders Research (28 papers). The work is most often cited by research in Genetics (367 citations), Cardiology and Cardiovascular Medicine (628 citations) and Cellular and Molecular Neuroscience (313 citations). Gianina Ravenscroft has collaborated with scholars based in Australia, United Kingdom and United States. Frequent co-authors include Nigel G. Laing, Kristen L. Nowak, Mark R. Davis, Sarah J. Beecroft, Elyshia McNamara, Phillipa J. Lamont, Carsten G. Bönnemann, Steven B. Marston, Connie Jackaman and Anthony J. Bakker. Their work appears in journals such as Journal of Clinical Investigation, PLoS ONE and Brain.
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.