Danielle Arbour

439 total citations
9 papers, 349 citations indexed

About

Danielle Arbour is a scholar working on Cellular and Molecular Neuroscience, Neurology and Genetics. According to data from OpenAlex, Danielle Arbour has authored 9 papers receiving a total of 349 indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Cellular and Molecular Neuroscience, 5 papers in Neurology and 4 papers in Genetics. Recurrent topics in Danielle Arbour's work include Amyotrophic Lateral Sclerosis Research (5 papers), Neurogenetic and Muscular Disorders Research (4 papers) and Nerve injury and regeneration (4 papers). Danielle Arbour is often cited by papers focused on Amyotrophic Lateral Sclerosis Research (5 papers), Neurogenetic and Muscular Disorders Research (4 papers) and Nerve injury and regeneration (4 papers). Danielle Arbour collaborates with scholars based in Canada. Danielle Arbour's co-authors include Richard Robitaille, Jean‐François Poulin, Guy Drolet, Sylvie Laforest, Éric Martineau, Houssam Darabid, Christine Vande Velde, Jean‐Pierre Julien, Joanne Vallée and Isabelle Rousse and has published in prestigious journals such as Journal of Neuroscience, The Journal of Physiology and Glia.

In The Last Decade

Danielle Arbour

9 papers receiving 349 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Danielle Arbour Canada 6 212 130 123 93 50 9 349
Steven R. DeGroot United States 5 238 1.1× 313 2.4× 192 1.6× 109 1.2× 74 1.5× 5 546
Sophia T. Papadeas United States 8 223 1.1× 214 1.6× 169 1.4× 83 0.9× 59 1.2× 8 491
Isabelle Rousse Canada 8 209 1.0× 109 0.8× 39 0.3× 18 0.2× 31 0.6× 10 325
Laura Cardoit France 11 153 0.7× 58 0.4× 116 0.9× 17 0.2× 54 1.1× 22 352
Fergil Mills Canada 8 146 0.7× 122 0.9× 96 0.8× 13 0.1× 50 1.0× 9 351
Andrés Montefeltro Spain 9 261 1.2× 189 1.5× 145 1.2× 14 0.2× 48 1.0× 9 469
Mehdi Hossaini Netherlands 10 158 0.7× 90 0.7× 90 0.7× 31 0.3× 36 0.7× 11 364
Marcin Maj Poland 12 271 1.3× 276 2.1× 56 0.5× 13 0.1× 25 0.5× 16 512
Marcelo D. Rosato‐Siri Italy 14 313 1.5× 268 2.1× 43 0.3× 15 0.2× 61 1.2× 17 482
Ivan Rattray United Kingdom 11 240 1.1× 228 1.8× 101 0.8× 7 0.1× 33 0.7× 15 431

Countries citing papers authored by Danielle Arbour

Since Specialization
Citations

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

Fields of papers citing papers by Danielle Arbour

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Danielle Arbour

This figure shows the co-authorship network connecting the top 25 collaborators of Danielle Arbour. A scholar is included among the top collaborators of Danielle Arbour 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 Danielle Arbour. Danielle Arbour 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.
Fiore, Frédéric Di, Nancy Larochelle, Danielle Arbour, et al.. (2024). Reversal of cognitive deficits in FUSR521G amyotrophic lateral sclerosis mice by arimoclomol and a class I histone deacetylase inhibitor independent of heat shock protein induction. Neurotherapeutics. 21(5). e00388–e00388. 3 indexed citations
2.
Rousse, Isabelle, et al.. (2022). Functional adaptation of glial cells at neuromuscular junctions in response to injury. Glia. 70(9). 1605–1629. 15 indexed citations
3.
Arbour, Danielle, et al.. (2021). hnRNP A1B, a Splice Variant of HNRNPA1, Is Spatially and Temporally Regulated. Frontiers in Neuroscience. 15. 724307–724307. 5 indexed citations
4.
Martineau, Éric, Danielle Arbour, Joanne Vallée, & Richard Robitaille. (2020). Properties of Glial Cell at the Neuromuscular Junction Are Incompatible with Synaptic Repair in the SOD1 G37R ALS Mouse Model. Journal of Neuroscience. 40(40). 7759–7777. 34 indexed citations
5.
Arbour, Danielle, Christine Vande Velde, & Richard Robitaille. (2016). New perspectives on amyotrophic lateral sclerosis: the role of glial cells at the neuromuscular junction. The Journal of Physiology. 595(3). 647–661. 57 indexed citations
6.
Arbour, Danielle, et al.. (2015). Early and Persistent Abnormal Decoding by Glial Cells at the Neuromuscular Junction in an ALS Model. Journal of Neuroscience. 35(2). 688–706. 75 indexed citations
7.
Darabid, Houssam, Danielle Arbour, & Richard Robitaille. (2013). Glial Cells Decipher Synaptic Competition at the Mammalian Neuromuscular Junction. Journal of Neuroscience. 33(4). 1297–1313. 54 indexed citations
8.
Arbour, Danielle, et al.. (2010). Computational simulation of vasopressin secretion using a rat model of the water and electrolyte homeostasis. BMC Physiology. 10(1). 17–17. 2 indexed citations
9.
Poulin, Jean‐François, Danielle Arbour, Sylvie Laforest, & Guy Drolet. (2009). Neuroanatomical characterization of endogenous opioids in the bed nucleus of the stria terminalis. Progress in Neuro-Psychopharmacology and Biological Psychiatry. 33(8). 1356–1365. 104 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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