Gabrielle Perron

626 total citations
11 papers, 370 citations indexed

About

Gabrielle Perron is a scholar working on Molecular Biology, Surgery and Physiology. According to data from OpenAlex, Gabrielle Perron has authored 11 papers receiving a total of 370 indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Molecular Biology, 3 papers in Surgery and 3 papers in Physiology. Recurrent topics in Gabrielle Perron's work include RNA modifications and cancer (4 papers), RNA Research and Splicing (4 papers) and Muscle Physiology and Disorders (2 papers). Gabrielle Perron is often cited by papers focused on RNA modifications and cancer (4 papers), RNA Research and Splicing (4 papers) and Muscle Physiology and Disorders (2 papers). Gabrielle Perron collaborates with scholars based in Canada, United States and Germany. Gabrielle Perron's co-authors include Jack P. Antel, Luke M. Healy, Craig S. Moore, Amit Bar‐Or, Mackenzie A. Michell‐Robinson, Ayman Rezk, Jeffery A. Hall, Samuel K. Ludwin, Khalil Bouyakdan and Jennifer L. Estall and has published in prestigious journals such as Nature Communications, The Journal of Immunology and Diabetes.

In The Last Decade

Gabrielle Perron

11 papers receiving 366 citations

Peers

Gabrielle Perron

IMMUN

NEURO

SURGE

PHYSI

Kyoko Suzuki-Utsunomiya Japan

Xiaoyi Shao China

Zhanfeng Liang China

Kongyan Niu China

Daniel Žucha Czechia

Mingfei Zhao China

Orie Nakamura Japan

Mitsuji Kaji Japan

Lin-Jing Li China

Kyoko Suzuki-Utsunomiya Japan

Gabrielle Perron

225 ×1.3

126 ×1.2

IMMUN

81 ×0.8

NEURO

33 ×0.4

SURGE

71 ×1.2

PHYSI

Citations per year, relative to Gabrielle Perron Gabrielle Perron (= 1×) peers Kyoko Suzuki-Utsunomiya

Countries citing papers authored by Gabrielle Perron

Since Specialization

Citations

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

Fields of papers citing papers by Gabrielle Perron

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Gabrielle Perron

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

All Works

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11 of 11 papers shown

Richard, Vincent R., Gabrielle Perron, René P. Zahedi, et al.. (2024). The E3 ubiquitin ligase Nedd4L preserves skeletal muscle stem cell quiescence by inhibiting their activation. iScience. 27(7). 110241–110241. 1 indexed citations

Thivierge, Caroline, Boris J.A. Dyakov, Rania Leventis, et al.. (2024). Paraspeckle-independent co-transcriptional regulation of nuclear microRNA biogenesis by SFPQ. Cell Reports. 43(9). 114695–114695. 3 indexed citations

Ray, Debashish, Kaitlin U. Laverty, Arttu Jolma, et al.. (2023). RNA-binding proteins that lack canonical RNA-binding domains are rarely sequence-specific. Scientific Reports. 13(1). 5238–5238. 24 indexed citations

Farouni, Rick, Gabrielle Perron, Tianyuan Lu, et al.. (2023). Transcriptional reprogramming of skeletal muscle stem cells by the niche environment. Nature Communications. 14(1). 535–535. 15 indexed citations

Perron, Gabrielle, Pouria Jandaghi, Elham Moslemi, et al.. (2022). Pan-cancer analysis of mRNA stability for decoding tumour post-transcriptional programs. Communications Biology. 5(1). 851–851. 9 indexed citations

Perron, Gabrielle, Pouria Jandaghi, Mehran Karimzadeh, et al.. (2018). A General Framework for Interrogation of mRNA Stability Programs Identifies RNA-Binding Proteins that Govern Cancer Transcriptomes. Cell Reports. 23(6). 1639–1650. 50 indexed citations

Healy, Luke M., Gabrielle Perron, Mackenzie A. Michell‐Robinson, et al.. (2016). MerTK Is a Functional Regulator of Myelin Phagocytosis by Human Myeloid Cells. The Journal of Immunology. 196(8). 3375–3384. 121 indexed citations

Pham, Tram N. Q., Sabelo Lukhele, Frédéric Dallaire, Gabrielle Perron, & Éric A. Cohen. (2016). Enhancing Virion Tethering by BST2 Sensitizes Productively and Latently HIV-infected T cells to ADCC Mediated by Broadly Neutralizing Antibodies. Scientific Reports. 6(1). 37225–37225. 18 indexed citations

Healy, Luke M., Gabrielle Perron, Vijayaraghava T.S. Rao, et al.. (2016). Differential transcriptional response profiles in human myeloid cell populations. Clinical Immunology. 189. 63–74. 18 indexed citations

10.

Oropeza, Daniel, Nathalie Jouvet, Khalil Bouyakdan, et al.. (2015). PGC-1 coactivators in β-cells regulate lipid metabolism and are essential for insulin secretion coupled to fatty acids. Molecular Metabolism. 4(11). 811–822. 48 indexed citations

11.

Oropeza, Daniel, Nathalie Jouvet, Lionel Budry, et al.. (2015). Phenotypic Characterization of MIP-CreERT1Lphi Mice With Transgene-Driven Islet Expression of Human Growth Hormone. Diabetes. 64(11). 3798–3807. 63 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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