Éric Audemard

1.0k total citations · 1 hit paper
9 papers, 664 citations indexed

About

Éric Audemard is a scholar working on Molecular Biology, Immunology and Genetics. According to data from OpenAlex, Éric Audemard has authored 9 papers receiving a total of 664 indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Molecular Biology, 3 papers in Immunology and 2 papers in Genetics. Recurrent topics in Éric Audemard's work include Acute Myeloid Leukemia Research (2 papers), Extracellular vesicles in disease (2 papers) and Retinoids in leukemia and cellular processes (2 papers). Éric Audemard is often cited by papers focused on Acute Myeloid Leukemia Research (2 papers), Extracellular vesicles in disease (2 papers) and Retinoids in leukemia and cellular processes (2 papers). Éric Audemard collaborates with scholars based in Canada, United States and France. Éric Audemard's co-authors include Shilpa Chennakrishnaiah, Brian Meehan, Laura Montermini, Janusz Rak, Tae Hoon Lee, Patrick Gendron, Sébastien Lemieux, Claude Perreault, Marie‐Pierre Hardy and Élie Haddad and has published in prestigious journals such as Blood, Cancer Research and Oncogene.

In The Last Decade

Éric Audemard

9 papers receiving 653 citations

Hit Papers

Noncoding regions are the main source of targetable tumor... 2018 2026 2020 2023 2018 100 200 300

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Éric Audemard Canada 7 483 265 209 188 58 9 664
Erica Hansen United States 7 445 0.9× 213 0.8× 121 0.6× 108 0.6× 35 0.6× 11 618
Karel Fostier Belgium 13 455 0.9× 263 1.0× 245 1.2× 194 1.0× 24 0.4× 25 738
Annie De Smet France 10 530 1.1× 259 1.0× 114 0.5× 100 0.5× 40 0.7× 13 708
Nasrin Rastgoo Canada 12 315 0.7× 177 0.7× 109 0.5× 130 0.7× 18 0.3× 25 551
Naiyan Zeng China 15 260 0.5× 163 0.6× 118 0.6× 185 1.0× 85 1.5× 22 602
S. M. Shahjahan Miah United States 18 267 0.6× 393 1.5× 61 0.3× 128 0.7× 78 1.3× 23 665
Claire Mazumdar United States 4 241 0.5× 316 1.2× 90 0.4× 289 1.5× 14 0.2× 4 585
Theresa A. Colligon United States 8 278 0.6× 319 1.2× 123 0.6× 297 1.6× 19 0.3× 11 705
Brice Laffleur France 14 285 0.6× 237 0.9× 65 0.3× 53 0.3× 61 1.1× 29 497
Nadine Kutsch Germany 9 166 0.3× 167 0.6× 92 0.4× 127 0.7× 48 0.8× 34 461

Countries citing papers authored by Éric Audemard

Since Specialization
Citations

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

Fields of papers citing papers by Éric Audemard

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Éric Audemard

This figure shows the co-authorship network connecting the top 25 collaborators of Éric Audemard. A scholar is included among the top collaborators of Éric Audemard 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 Éric Audemard. Éric Audemard is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

9 of 9 papers shown
1.
Lisi, Véronique, Éric Audemard, Sébastien Lemieux, et al.. (2022). Unified gene expression signature of novel NPM1 exon 5 mutations in acute myeloid leukemia. Blood Advances. 6(17). 5160–5164. 1 indexed citations
2.
Simon, Laura, Jean-François Spinella, Chi‐Yuan Yao, et al.. (2020). High frequency of germline RUNX1 mutations in patients with RUNX1-mutated AML. Blood. 135(21). 1882–1886. 51 indexed citations
3.
Audemard, Éric, Patrick Gendron, Vincent‐Philippe Lavallée, et al.. (2019). Targeted variant detection using unaligned RNA-Seq reads. Life Science Alliance. 2(4). e201900336–e201900336. 13 indexed citations
4.
Hardy, Marie‐Pierre, Éric Audemard, Francis Migneault, et al.. (2019). Apoptotic endothelial cells release small extracellular vesicles loaded with immunostimulatory viral-like RNAs. Scientific Reports. 9(1). 7203–7203. 57 indexed citations
5.
Dumeaux, Vanessa, et al.. (2018). Role of SUMOylation in differential ERα transcriptional repression by tamoxifen and fulvestrant in breast cancer cells. Oncogene. 38(7). 1019–1037. 31 indexed citations
6.
Laumont, Céline M., Krystel Vincent, Leslie Hesnard, et al.. (2018). Noncoding regions are the main source of targetable tumor-specific antigens. Science Translational Medicine. 10(470). 335 indexed citations breakdown →
7.
Mathieu, Mélissa, Sandy Pelletier, Steven Hébert, et al.. (2018). Abstract 4670: Evidence of neoantigen-reactive T cell response in a case of relapsing, mismatch-repair gene proficient, colorectal cancer. Cancer Research. 78(13_Supplement). 4670–4670. 1 indexed citations
8.
Lee, Tae Hoon, Shilpa Chennakrishnaiah, Éric Audemard, et al.. (2014). Oncogenic ras-driven cancer cell vesiculation leads to emission of double-stranded DNA capable of interacting with target cells. Biochemical and Biophysical Research Communications. 451(2). 295–301. 169 indexed citations
9.
Audemard, Éric, Thomas Schiex, & Thomas Faraut. (2012). Detecting long tandem duplications in genomic sequences. BMC Bioinformatics. 13(1). 6 indexed citations

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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