Mathieu Gravel
About
In The Last Decade
Mathieu Gravel
10 papers receiving 429 citations
Peers
Comparison fields: 5 of 64
- Neurology 198
- Molecular Biology 165
- Neurology 128
- Genetics 108
- Cellular and Molecular Neuroscience 73
Countries citing papers authored by Mathieu Gravel
This map shows the geographic impact of Mathieu Gravel'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 Mathieu Gravel with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Mathieu Gravel more than expected).
Fields of papers citing papers by Mathieu Gravel
This network shows the impact of papers produced by Mathieu Gravel. 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 Mathieu Gravel. The network helps show where Mathieu Gravel may publish in the future.
Co-authorship network of co-authors of Mathieu Gravel
This figure shows the co-authorship network connecting the top 25 collaborators of Mathieu Gravel. A scholar is included among the top collaborators of Mathieu Gravel 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 Mathieu Gravel. Mathieu Gravel is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 2 | |
| 2 | 1 | |
| 3 | 7 | |
| 4 | 85 | |
| 5 | 94 | |
| 6 | 15 | |
| 7 | 1 | |
| 8 | 71 | |
| 9 | 80 | |
| 10 | 73 |
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.