Hélène Tran

2.0k total citations · 1 hit paper
16 papers, 933 citations indexed

About

Hélène Tran is a scholar working on Molecular Biology, Neurology and Cellular and Molecular Neuroscience. According to data from OpenAlex, Hélène Tran has authored 16 papers receiving a total of 933 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Molecular Biology, 8 papers in Neurology and 6 papers in Cellular and Molecular Neuroscience. Recurrent topics in Hélène Tran's work include Amyotrophic Lateral Sclerosis Research (7 papers), Genetic Neurodegenerative Diseases (6 papers) and Neurogenetic and Muscular Disorders Research (4 papers). Hélène Tran is often cited by papers focused on Amyotrophic Lateral Sclerosis Research (7 papers), Genetic Neurodegenerative Diseases (6 papers) and Neurogenetic and Muscular Disorders Research (4 papers). Hélène Tran collaborates with scholars based in France, United States and Spain. Hélène Tran's co-authors include Fen‐Biao Gao, Leonard Petrucelli, Tania F. Gendron, Sandra Almeida, Anna Karydas, Bruce L. Miller, Yubing Lu, Dejun Yang, Chantal Sellier and Steven R. DeGroot and has published in prestigious journals such as Neuron, FEBS Letters and Human Molecular Genetics.

In The Last Decade

Hélène Tran

15 papers receiving 923 citations

Hit Papers

Poly(GR) in C9ORF72 -Related ALS/FTD Compromises Mitochon... 2016 2026 2019 2022 2016 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
Hélène Tran France 10 616 523 332 241 134 16 933
André Bento‐Abreu Belgium 12 372 0.6× 383 0.7× 231 0.7× 171 0.7× 118 0.9× 18 833
Anissa Fergani France 10 635 1.0× 271 0.5× 373 1.1× 157 0.7× 141 1.1× 10 843
Birgit Schwalenstöcker Germany 13 436 0.7× 327 0.6× 289 0.9× 248 1.0× 89 0.7× 16 745
Jenna M. Gregory United Kingdom 15 474 0.8× 346 0.7× 229 0.7× 99 0.4× 153 1.1× 38 739
Stan Atkin United States 6 256 0.4× 408 0.8× 165 0.5× 143 0.6× 102 0.8× 7 747
Emma F. Smith United Kingdom 6 569 0.9× 346 0.7× 247 0.7× 132 0.5× 187 1.4× 6 849
Franck Patin France 16 426 0.7× 270 0.5× 204 0.6× 76 0.3× 133 1.0× 25 721
Rachel A.K. Atkinson Australia 10 408 0.7× 236 0.5× 198 0.6× 91 0.4× 166 1.2× 16 638
Monica Nencini Italy 12 563 0.9× 360 0.7× 238 0.7× 110 0.5× 145 1.1× 14 803
Kerstin E. Braunstein United States 13 267 0.4× 275 0.5× 159 0.5× 97 0.4× 130 1.0× 13 581

Countries citing papers authored by Hélène Tran

Since Specialization
Citations

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

Fields of papers citing papers by Hélène Tran

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Hélène Tran

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

All Works

16 of 16 papers shown
1.
Krupp, Johannes, et al.. (2024). Voltage-Gated Ion Channel Compensatory Effect in DEE: Implications for Future Therapies. Cells. 13(21). 1763–1763.
2.
Verreault, Maïté, et al.. (2024). Clinical Applications of Antisense Oligonucleotides in Cancer: A Focus on Glioblastoma. Cells. 13(22). 1869–1869. 12 indexed citations
3.
Gilbert, James W., Zachary Kennedy, Bruno M.D.C. Godinho, et al.. (2024). Identification of selective and non-selective C9ORF72 targeting in vivo active siRNAs. Molecular Therapy — Nucleic Acids. 35(3). 102291–102291. 3 indexed citations
4.
Cabrera, Gabriela Toro, Katharina E. Meijboom, Hélène Tran, et al.. (2023). Artificial microRNA suppresses C9ORF72 variants and decreases toxic dipeptide repeat proteins in vivo. Gene Therapy. 31(3-4). 105–118. 5 indexed citations
5.
Arandel, Ludovic, Arnaud F. Klein, Frédérique Rau, et al.. (2022). Reversal of RNA toxicity in myotonic dystrophy via a decoy RNA-binding protein with high affinity for expanded CUG repeats. Nature Biomedical Engineering. 6(2). 207–220. 25 indexed citations
6.
Tran, Hélène, Sébastien Guillaume, Dominique Delaunay, et al.. (2020). FOOD ADDICTION AS A PROXY FOR ANOREXIA NERVOSA SEVERITY: NEW DATA BASED ON THE YALE FOOD ADDICTION SCALE 2.0. Psychiatry Research. 293. 113472–113472. 29 indexed citations
7.
Fernández-Gómez, Francisco-José, Hélène Tran, Claire‐Marie Dhaenens, et al.. (2019). Myotonic Dystrophy: an RNA Toxic Gain of Function Tauopathy?. Advances in experimental medicine and biology. 1184. 207–216. 13 indexed citations
8.
Tran, Hélène, et al.. (2017). A Drosophila model of ALS reveals a partial loss of function of causative human PFN1 mutants. Human Molecular Genetics. 26(11). 2146–2155. 11 indexed citations
9.
Lu, Yubing, Tania F. Gendron, Anna Karydas, et al.. (2016). Poly(GR) in C9ORF72 -Related ALS/FTD Compromises Mitochondrial Function and Increases Oxidative Stress and DNA Damage in iPSC-Derived Motor Neurons. Neuron. 92(2). 383–391. 315 indexed citations breakdown →
10.
Tran, Hélène, Sandra Almeida, Jill E. Moore, et al.. (2015). Differential Toxicity of Nuclear RNA Foci versus Dipeptide Repeat Proteins in a Drosophila Model of C9ORF72 FTD/ALS. Neuron. 87(6). 1207–1214. 144 indexed citations
11.
Caillet‐Boudin, Marie‐Laure, Francisco-José Fernández-Gómez, Hélène Tran, et al.. (2014). Brain pathology in myotonic dystrophy: when tauopathy meets spliceopathy and RNAopathy. Frontiers in Molecular Neuroscience. 6. 57–57. 73 indexed citations
12.
Fernández-Gómez, Francisco-José, Fanny Jumeau, Maxime Derisbourg, et al.. (2014). Consensus Brain-derived Protein, Extraction Protocol for the Study of Human and Murine Brain Proteome Using Both 2D-DIGE and Mini 2DE Immunoblotting. Journal of Visualized Experiments. 5 indexed citations
13.
Fernández-Gómez, Francisco-José, Fanny Jumeau, Maxime Derisbourg, et al.. (2014). Consensus Brain-derived Protein, Extraction Protocol for the Study of Human and Murine Brain Proteome Using Both 2D-DIGE and Mini 2DE Immunoblotting. Journal of Visualized Experiments. 1 indexed citations
14.
Almeida, Sandra, Eduardo Gascon, Hélène Tran, et al.. (2013). Modeling key pathological features of frontotemporal dementia with C9ORF72 repeat expansion in iPSC-derived human neurons. Acta Neuropathologica. 126(3). 385–399. 251 indexed citations
15.
Bevans, Carville G., et al.. (2013). Determination of the warfarin inhibition constant Ki for vitamin K 2,3-epoxide reductase complex subunit-1 (VKORC1) using an in vitro DTT-driven assay. Biochimica et Biophysica Acta (BBA) - General Subjects. 1830(8). 4202–4210. 38 indexed citations
16.
Ghanem, Dana, Hélène Tran, Claire‐Marie Dhaenens, et al.. (2009). Altered splicing of Tau in DM1 is different from the foetal splicing process. FEBS Letters. 583(4). 675–679. 8 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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