Marc Aubry

2.0k citations
50 papers · 1.5k indexed · h-index 22

Impact in

  • Genetics top 2%
    • Glioma Diagnosis and Treatment
    • MicroRNA in disease regulation
    • Cancer-related molecular mechanisms research
    • Cancer Genomics and Diagnostics

Papers in

    • Glioma Diagnosis and Treatment 18
    • MicroRNA in disease regulation 9
    • Cancer Genomics and Diagnostics 4

Marc Aubry

49 papers receiving 1.5k citations

Peers

Marc Aubry
Comparison fields: 5 of 118
  • Genetics 355
  • Cancer Research 412
  • Molecular Biology 866
  • Biophysics 60
  • Oncology 187
Replace Toma Tebaldi with:
Toma Tebaldi Italy
Armand Bankhead United States
Nicola Johnson United Kingdom
Karlyne M. Reilly United States
Daciana Margineantu United States
Lorella Vecchio Italy
Junfei Zhao United States
Edwin Wang Canada
Qian Qin China
Shenghong Ma United States
Marc Aubry relative to Toma Tebaldi Italy Toma Tebaldi's profile →
Citations per field
00.5×1.5×1.8×
Toma Tebaldi · 1×
Citations per year

Countries citing papers authored by Marc Aubry

Since Specialization
Citations

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

Fields of papers citing papers by Marc Aubry

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

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

All Works

20 of 20 papers shown
#Work
1 20251
2 20250
3 202421
4 20234
5 20224
6 20224
7 202121
8 202110
9 202016
10 201929
11 201913
12 201823
13 201810
14 20156
15 201419
16 201448
17 201242
18 201162
19 201130
20 2010179

About Marc Aubry

Marc Aubry is a scholar working on Genetics, Cancer Research, Structural Biology, Hematology and Biophysics, having authored 50 papers that have together received 1.5k indexed citations. Recurring topics across this work include Glioma Diagnosis and Treatment (18 papers), MicroRNA in disease regulation (9 papers), Epigenetics and DNA Methylation (9 papers), Iron Metabolism and Disorders (5 papers), RNA modifications and cancer (5 papers), Ferroptosis and cancer prognosis (4 papers), Cancer Genomics and Diagnostics (4 papers) and Radiomics and Machine Learning in Medical Imaging (4 papers). The work is most often cited by research in Genetics (355 citations), Cancer Research (412 citations), Molecular Biology (866 citations), Biophysics (60 citations) and Oncology (187 citations). Marc Aubry has collaborated with scholars based in France, China and United States. Frequent co-authors include Jean Mosser, Marie de Tayrac, Amandine Etcheverry, Philippe Meneï, Stéphan Saïkali, Véronique Quillien, Abderrahmane Hamlat, Anita Burgun, Olivier Bodenreider and Marie‐Dominique Galibert. Their work appears in journals such as PLoS ONE, Scientific Reports, Oncotarget, BMC Genomics and Clinical Epigenetics.

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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