Loic Auderset

470 total citations
9 papers, 326 citations indexed

About

Loic Auderset is a scholar working on Molecular Biology, Cellular and Molecular Neuroscience and Developmental Neuroscience. According to data from OpenAlex, Loic Auderset has authored 9 papers receiving a total of 326 indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Molecular Biology, 3 papers in Cellular and Molecular Neuroscience and 3 papers in Developmental Neuroscience. Recurrent topics in Loic Auderset's work include Neurogenesis and neuroplasticity mechanisms (3 papers), Signaling Pathways in Disease (2 papers) and Extracellular vesicles in disease (2 papers). Loic Auderset is often cited by papers focused on Neurogenesis and neuroplasticity mechanisms (3 papers), Signaling Pathways in Disease (2 papers) and Extracellular vesicles in disease (2 papers). Loic Auderset collaborates with scholars based in Australia, Germany and Switzerland. Loic Auderset's co-authors include Kaylene M. Young, Carlie L. Cullen, Jennifer Rodger, Alexander D. Tang, Megan E. O’Rourke, Lisa Foa, Kimberley A. Pitman, Anna Antoniou, Jan Gründemann and Ben Emery and has published in prestigious journals such as PLoS ONE, Cell Reports and Glia.

In The Last Decade

Loic Auderset

8 papers receiving 324 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Loic Auderset Australia	8	124	115	93	84	55	9	326
Ryusuke Suzuki Japan	10	73 0.6×	146 1.3×	119 1.3×	98 1.2×	49 0.9×	18	357
Seulgi Noh South Korea	6	165 1.3×	93 0.8×	66 0.7×	118 1.4×	65 1.2×	8	340
Georg L. Wieser Germany	7	84 0.7×	134 1.2×	140 1.5×	128 1.5×	29 0.5×	7	378
Elena Giusto United Kingdom	10	102 0.8×	203 1.8×	81 0.9×	94 1.1×	61 1.1×	16	438
Sarah‐Ann Aelvoet Belgium	7	107 0.9×	180 1.6×	163 1.8×	163 1.9×	59 1.1×	7	442
Jagroop Dhaliwal Canada	9	84 0.7×	127 1.1×	157 1.7×	74 0.9×	28 0.5×	11	309
Nimmi Baby Singapore	9	155 1.3×	114 1.0×	60 0.6×	123 1.5×	64 1.2×	10	344
Guangdan Yu China	8	211 1.7×	137 1.2×	176 1.9×	57 0.7×	47 0.9×	11	402
Sylvia Agathou United Kingdom	6	154 1.2×	191 1.7×	197 2.1×	153 1.8×	70 1.3×	8	450

Countries citing papers authored by Loic Auderset

Since Specialization

Citations

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

Fields of papers citing papers by Loic Auderset

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Loic Auderset

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

All Works

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9 of 9 papers shown

Auderset, Loic & Anna Antoniou. (2023). EVs from primary neurons: Characterization of extracellular vesicles derived from mouse primary neurons. 5(1). 20–27.

Antoniou, Anna, Loic Auderset, Lalit Kaurani, et al.. (2023). Neuronal extracellular vesicles and associated microRNAs induce circuit connectivity downstream BDNF. Cell Reports. 42(2). 112063–112063. 55 indexed citations

Cullen, Carlie L., Kimberley A. Pitman, Viola Oorschot, et al.. (2021). Periaxonal and nodal plasticities modulate action potential conduction in the adult mouse brain. Cell Reports. 34(3). 108641–108641. 57 indexed citations

Auderset, Loic, Kimberley A. Pitman, Carlie L. Cullen, et al.. (2020). Low-Density Lipoprotein Receptor-Related Protein 1 (LRP1) Is a Negative Regulator of Oligodendrocyte Progenitor Cell Differentiation in the Adult Mouse Brain. Frontiers in Cell and Developmental Biology. 8. 564351–564351. 24 indexed citations

Cullen, Carlie L., Megan E. O’Rourke, Loic Auderset, et al.. (2020). Kif3a deletion prevents primary cilia assembly on oligodendrocyte progenitor cells, reduces oligodendrogenesis and impairs fine motor function. Glia. 69(5). 1184–1203. 21 indexed citations

Cullen, Carlie L., Alexander D. Tang, Loic Auderset, et al.. (2019). Low‐intensity transcranial magnetic stimulation promotes the survival and maturation of newborn oligodendrocytes in the adult mouse brain. Glia. 67(8). 1462–1477. 65 indexed citations

Auderset, Loic, et al.. (2016). Low Density Lipoprotein Receptor Related Proteins as Regulators of Neural Stem and Progenitor Cell Function. Stem Cells International. 2016(1). 2108495–2108495. 37 indexed citations

O’Rourke, Megan E., Carlie L. Cullen, Loic Auderset, et al.. (2016). Evaluating Tissue-Specific Recombination in a Pdgfrα-CreERT2 Transgenic Mouse Line. PLoS ONE. 11(9). e0162858–e0162858. 18 indexed citations

Auderset, Loic, Carlie L. Cullen, & Kaylene M. Young. (2016). Low Density Lipoprotein-Receptor Related Protein 1 Is Differentially Expressed by Neuronal and Glial Populations in the Developing and Mature Mouse Central Nervous System. PLoS ONE. 11(6). e0155878–e0155878. 49 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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