Emmanuelle Querido

3.3k total citations · 1 hit paper
24 papers, 2.7k citations indexed

About

Emmanuelle Querido is a scholar working on Molecular Biology, Oncology and Physiology. According to data from OpenAlex, Emmanuelle Querido has authored 24 papers receiving a total of 2.7k indexed citations (citations by other indexed papers that have themselves been cited), including 21 papers in Molecular Biology, 8 papers in Oncology and 7 papers in Physiology. Recurrent topics in Emmanuelle Querido's work include Cancer-related Molecular Pathways (7 papers), Telomeres, Telomerase, and Senescence (7 papers) and Virus-based gene therapy research (6 papers). Emmanuelle Querido is often cited by papers focused on Cancer-related Molecular Pathways (7 papers), Telomeres, Telomerase, and Senescence (7 papers) and Virus-based gene therapy research (6 papers). Emmanuelle Querido collaborates with scholars based in Canada, United States and Italy. Emmanuelle Querido's co-authors include Gerardo Ferbeyre, Scott W. Lowe, Philip E. Branton, Elisa de Stanchina, Pascal Chartrand, Carol Prives, Nicole Baptiste, Dominique Boivin, Véronique Bourdeau and Vincent De Guire and has published in prestigious journals such as Nucleic Acids Research, Journal of Biological Chemistry and Genes & Development.

In The Last Decade

Emmanuelle Querido

22 papers receiving 2.7k citations

Hit Papers

Degradation of p53 by adenovirus E4orf6 and E1B55K protei... 2001 2026 2009 2017 2001 100 200 300 400

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Emmanuelle Querido Canada 17 2.2k 872 727 576 418 24 2.7k
Vincent Moncollin France 25 3.9k 1.7× 873 1.0× 709 1.0× 535 0.9× 206 0.5× 38 4.5k
Vinod Pant United States 20 2.3k 1.0× 763 0.9× 712 1.0× 339 0.6× 119 0.3× 36 2.8k
Guillermo E. Taccioli United States 26 3.9k 1.8× 1.2k 1.4× 363 0.5× 681 1.2× 445 1.1× 39 4.9k
Ho Man Chan United States 14 2.3k 1.0× 737 0.8× 333 0.5× 289 0.5× 94 0.2× 24 2.7k
Anthony G. Uren United Kingdom 22 2.5k 1.1× 598 0.7× 378 0.5× 445 0.8× 112 0.3× 32 3.1k
Mandy Madiredjo Netherlands 8 2.4k 1.1× 1.2k 1.4× 308 0.4× 533 0.9× 95 0.2× 8 3.2k
Phillip B. Carpenter United States 23 3.6k 1.6× 1.0k 1.2× 398 0.5× 610 1.1× 208 0.5× 31 4.0k
Jianyuan Luo United States 8 2.2k 1.0× 1.2k 1.4× 185 0.3× 297 0.5× 101 0.2× 9 2.6k
Lee H. Wong Australia 33 3.4k 1.5× 688 0.8× 710 1.0× 297 0.5× 255 0.6× 57 4.3k
Yunmei Ma United States 18 3.0k 1.4× 857 1.0× 365 0.5× 526 0.9× 113 0.3× 22 3.4k

Countries citing papers authored by Emmanuelle Querido

Since Specialization
Citations

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

Fields of papers citing papers by Emmanuelle Querido

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Emmanuelle Querido

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

All Works

20 of 20 papers shown
2.
Querido, Emmanuelle, et al.. (2024). TERRA transcripts localize at long telomeres to regulate telomerase access to chromosome ends. Science Advances. 10(24). eadk4387–eadk4387. 8 indexed citations
3.
Querido, Emmanuelle, et al.. (2023). Phosphorylation controls the oligomeric state of She2 and mRNA localization in yeast. RNA. 29(6). 745–755.
4.
Smith, Michael J., Emmanuelle Querido, Pascal Chartrand, & Agnel Sfeir. (2020). Quantitative Imaging of MS2-Tagged hTR in Cajal Bodies: Photobleaching and Photoactivation. STAR Protocols. 1(3). 100112–100112. 1 indexed citations
5.
Querido, Emmanuelle, Agnel Sfeir, & Pascal Chartrand. (2020). Imaging of Telomerase RNA by Single-Molecule Inexpensive FISH Combined with Immunofluorescence. STAR Protocols. 1(2). 100104–100104. 6 indexed citations
6.
Querido, Emmanuelle, Michael J. Smith, David Guérit, et al.. (2020). Single-Molecule Imaging of Telomerase RNA Reveals a Recruitment-Retention Model for Telomere Elongation. Molecular Cell. 79(1). 115–126.e6. 40 indexed citations
7.
Querido, Emmanuelle, et al.. (2018). Live-cell imaging reveals the dynamics and function of single-telomere TERRA molecules in cancer cells. RNA Biology. 15(6). 1–10. 22 indexed citations
8.
Querido, Emmanuelle, et al.. (2017). RNA fluorescence in situ hybridization for high-content screening. Methods. 126. 149–155. 18 indexed citations
9.
Gallardo, Franck, et al.. (2011). Live Cell Imaging of Telomerase RNA Dynamics Reveals Cell Cycle-Dependent Clustering of Telomerase at Elongating Telomeres. Molecular Cell. 44(5). 819–827. 92 indexed citations
10.
Querido, Emmanuelle, Franck Gallardo, Mélissa Beaudoin, Catherine Ménard, & Pascal Chartrand. (2011). Stochastic and reversible aggregation of mRNA with expanded CUG-triplet repeats. Journal of Cell Science. 124(10). 1703–1714. 63 indexed citations
11.
Querido, Emmanuelle & Pascal Chartrand. (2008). Using Fluorescent Proteins to Study mRNA Trafficking in Living Cells. Methods in cell biology. 85. 273–292. 57 indexed citations
12.
Guire, Vincent De, Emmanuelle Querido, Utpal K. Mukhopadhyay, et al.. (2006). An E2F/miR-20a Autoregulatory Feedback Loop. Journal of Biological Chemistry. 282(4). 2135–2143. 481 indexed citations
13.
Stanchina, Elisa de, Emmanuelle Querido, Masako Narita, et al.. (2004). PML Is a Direct p53 Target that Modulates p53 Effector Functions. Molecular Cell. 13(4). 523–535. 246 indexed citations
14.
Ferbeyre, Gerardo, Elisa de Stanchina, Athena W. Lin, et al.. (2002). Oncogenic ras and p53 Cooperate To Induce Cellular Senescence. Molecular and Cellular Biology. 22(10). 3497–3508. 243 indexed citations
15.
Kamura, Takumi, Dennis Burian, Qin Yan, et al.. (2001). MUF1, A Novel Elongin BC-interacting Leucine-rich Repeat Protein That Can Assemble with Cul5 and Rbx1 to Reconstitute a Ubiquitin Ligase. Journal of Biological Chemistry. 276(32). 29748–29753. 138 indexed citations
16.
Querido, Emmanuelle, Paola Blanchette, Qin Yan, et al.. (2001). Degradation of p53 by adenovirus E4orf6 and E1B55K proteins occurs via a novel mechanism involving a Cullin-containing complex. Genes & Development. 15(23). 3104–3117. 410 indexed citations breakdown →
17.
Querido, Emmanuelle, et al.. (2001). Identification of Three Functions of the Adenovirus E4orf6 Protein That Mediate p53 Degradation by the E4orf6-E1B55K Complex. Journal of Virology. 75(5). 2508–2508. 5 indexed citations
18.
Querido, Emmanuelle, et al.. (2000). Identification and Elimination of an Aberrant Splice Product from cDNAs Encoding the Human Adenovirus Type 5 E4orf6 Protein. Virology. 275(2). 263–266. 5 indexed citations
20.
Bawab, Wafaa, Emmanuelle Querido, Philippe Crine, & Luc DesGroseillers. (1992). Identification and characterization of aminopeptidases from Aplysia californica. Biochemical Journal. 286(3). 967–975. 23 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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