Mathieu Daynac

830 citations
18 papers · 619 · h-index 14

Impact in

Papers in

Mathieu Daynac

17 papers receiving 617 citations

Peers

Mathieu Daynac
Comparison fields: 5 of 74
  • Developmental Neuroscience 286
  • Neurology 105
  • Aging 20
  • Genetics 91
  • Cancer Research 84
Replace Alexandra Chicheportiche with:
Alexandra Chicheportiche France
Daniel C. Factor United States
Cecilia Zuliani Germany
Thomas Wegleiter Switzerland
Abhijeet Pataskar Germany
Nathalie Saurat United States
April Kemper United States
Fernando C. Baltanás Spain
Anita Schlierf United States
Stéphane Genoud United States
Mathieu Daynac relative to Alexandra Chicheportiche France Alexandra Chicheportiche's profile →
Citations per field
00.5×1.6×
Alexandra Chicheportiche · 1×
Citations per year

Countries citing papers authored by Mathieu Daynac

Since Specialization
Citations

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

Fields of papers citing papers by Mathieu Daynac

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

18 of 18 papers shown
#Work
1 2013109
2 201670
3 201368
4 201855
5 201654
6 201447
7 202140
8 201134
9 201429
10 201624
11 201521
12 201520
13 201818
14 201714
15 202110
16 20174
17 20152
18 20210

About Mathieu Daynac

Mathieu Daynac is a scholar working on Molecular Biology, Developmental Neuroscience, Genetics, Oncology and Cancer Research, having authored 18 papers that have together received 619 indexed citations. Recurring topics across this work include Neurogenesis and neuroplasticity mechanisms (11 papers), Epigenetics and DNA Methylation (5 papers), Pluripotent Stem Cells Research (4 papers), MicroRNA in disease regulation (3 papers), Glioma Diagnosis and Treatment (3 papers), Neuroinflammation and Neurodegeneration Mechanisms (2 papers), Cancer Research and Treatments (2 papers) and Hedgehog Signaling Pathway Studies (2 papers). The work is most often cited by research in Developmental Neuroscience (286 citations), Neurology (105 citations), Aging (20 citations), Genetics (91 citations) and Cancer Research (84 citations). Mathieu Daynac has collaborated with scholars based in France, United States and Germany. Frequent co-authors include François D. Boussin, Marc‐André Mouthon, Alexandra Chicheportiche, Laurent Gauthier, Lise Morizur, José Ramón Pineda, Arantxa Cebrián‐Silla, José Manuel García‐Verdugo, Karine Sii-Felice and Martial Ruat. Their work appears in journals such as Journal of Visualized Experiments, Stem Cell Reports, Stem Cells, Scientific Reports and Nature Communications.

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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