Maéva Vignes

871 citations
11 papers · 671 · h-index 8

Impact in

    • Neuroscience and Neural Engineering
    • Photoreceptor and optogenetics research
    • 3D Printing in Biomedical Research
    • Innovative Microfluidic and Catalytic Techniques Innovation
    • Microfluidic and Bio-sensing Technologies

Papers in

Maéva Vignes

11 papers receiving 665 citations

Peers

Maéva Vignes
Comparison fields: 5 of 98
  • Cellular and Molecular Neuroscience 299
  • Biomedical Engineering 387
  • Molecular Medicine 34
  • Biophysics 23
  • Cognitive Neuroscience 67
Replace David A. Nagel with:
David A. Nagel United Kingdom
Tania Q. Vu United States
Jeremy Sauer United States
Shadi Damanpour United States
Gerhard Leinenga Australia
Mattia Pesce Italy
Emanuela Saracino Italy
Cecilia Ferrantini Italy
Ioanna Sandvig Norway
Hyun Jin Kim South Korea
Maéva Vignes relative to David A. Nagel United Kingdom David A. Nagel's profile →
Citations per field
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David A. Nagel · 1×
Citations per year

Countries citing papers authored by Maéva Vignes

Since Specialization
Citations

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

Fields of papers citing papers by Maéva Vignes

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Maéva Vignes, 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 Maéva Vignes Line = papers co-authored together Maéva Vignes links everyone, so they are left out of the graph.

All Works

11 of 11 papers shown
#Work
1 2011212
2 2013174
3 200981
4 201560
5 201452
6 201347
7 201628
8 20249
9 20143
10
MICROFLUIDIC CULTURE CHAMBER FOR THE LONG-TERM PERFU- SION AND PRECISE CHEMICAL STIMULATION OF ORGANOTYPIC BRAIN TISSUE SLICES
20103
11 20202

About Maéva Vignes

Maéva Vignes is a scholar working on Cellular and Molecular Neuroscience, Biomedical Engineering, Physiology, Oncology and Artificial Intelligence, having authored 11 papers that have together received 671 indexed citations. Recurring topics across this work include Neuroscience and Neural Engineering (7 papers), 3D Printing in Biomedical Research (4 papers), Photoreceptor and optogenetics research (3 papers), Neuroscience and Neuropharmacology Research (3 papers), Alzheimer's disease research and treatments (2 papers), Anesthesia and Neurotoxicity Research (1 paper), Sentiment Analysis and Opinion Mining (1 paper) and Trace Elements in Health (1 paper). The work is most often cited by research in Cellular and Molecular Neuroscience (299 citations), Biomedical Engineering (387 citations), Molecular Medicine (34 citations), Biophysics (23 citations) and Cognitive Neuroscience (67 citations). Maéva Vignes has collaborated with scholars based in France, United States and United Kingdom. Frequent co-authors include Jean‐Louis Viovy, Stéphanie Descroix, Laurent Malaquin, Jean‐Michel Peyrin, Danijela Matic Vignjevic, Marine Verhulsel, Bernard Brugg, Bérangère Deleglise, Sébastien Magnifico and Paul Gougis. Their work appears in journals such as PLoS ONE, Acta Neuropathologica Communications, Lab on a Chip, ChemBioChem and Biomaterials.

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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