Gabrielle Macaron

519 citations
29 papers · 320 · h-index 10

Impact in

Papers in

Gabrielle Macaron

25 papers receiving 315 citations

Peers

Gabrielle Macaron
Comparison fields: 5 of 61
  • Pathology and Forensic Medicine 187
  • Neurology 51
  • Nephrology 19
  • Neurology 18
  • Rheumatology 21
Replace José Meca-Lallana with:
José Meca-Lallana Spain
Martina Petruzzo Italy
Vittorio Mantero Italy
Véronique Bissay Belgium
L. G. F. Sinnige Netherlands
Jera Kruja Albania
Markus Ponleitner Austria
Salvatore Cottone Italy
Tamara Kaplan United States
Alexander Stahmann Germany
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Citations per field
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Citations per year

Countries citing papers authored by Gabrielle Macaron

Since Specialization
Citations

This map shows the geographic impact of Gabrielle Macaron'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 Gabrielle Macaron with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Gabrielle Macaron more than expected).

Fields of papers citing papers by Gabrielle Macaron

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Gabrielle Macaron. 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 Gabrielle Macaron. The network helps show where Gabrielle Macaron may publish in the future.

Co-authors

The 25 scholars most cited alongside Gabrielle Macaron, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Gabrielle Macaron Line = papers co-authored together Gabrielle Macaron links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 29 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201956
2 201332
3 202032
4 202030
5 202329
6 201924
7 201917
8 201917
9 201913
10 202110
11 20168
12 20217
13 20167
14 20196
15 20186
16 20226
17 20234
18 20254
19 20253
20 20212

About Gabrielle Macaron

Gabrielle Macaron is a scholar working on Pathology and Forensic Medicine, Neurology, Molecular Biology, Rheumatology and Oncology, having authored 29 papers that have together received 320 indexed citations. Recurring topics across this work include Multiple Sclerosis Research Studies (18 papers), Rheumatoid Arthritis Research and Therapies (3 papers), Peripheral Neuropathies and Disorders (3 papers), RNA regulation and disease (3 papers), Autoimmune Neurological Disorders and Treatments (2 papers), Polyomavirus and related diseases (2 papers), Neurogenesis and neuroplasticity mechanisms (1 paper) and Genetics and Neurodevelopmental Disorders (1 paper). The work is most often cited by research in Pathology and Forensic Medicine (187 citations), Neurology (51 citations), Nephrology (19 citations), Neurology (18 citations) and Rheumatology (21 citations). Gabrielle Macaron has collaborated with scholars based in United States, Lebanon and Canada. Frequent co-authors include Daniel Ontaneda, Mary Rensel, Jeffrey A. Cohen, Sami Richa, Stephen M. Rao, Manikum Moodley, Dany Matar, Brandon Moss, François Kazour and Laura Baldassari. Their work appears in journals such as Neurology, Multiple Sclerosis and Related Disorders, Multiple Sclerosis Journal, International Journal of MS Care and Journal of Neuroimmunology.

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.

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