Marcus Keatinge

1.5k total citations
22 papers, 953 citations indexed

About

Marcus Keatinge is a scholar working on Cell Biology, Molecular Biology and Neurology. According to data from OpenAlex, Marcus Keatinge has authored 22 papers receiving a total of 953 indexed citations (citations by other indexed papers that have themselves been cited), including 13 papers in Cell Biology, 10 papers in Molecular Biology and 8 papers in Neurology. Recurrent topics in Marcus Keatinge's work include Zebrafish Biomedical Research Applications (13 papers), Neuroinflammation and Neurodegeneration Mechanisms (7 papers) and Neurogenesis and neuroplasticity mechanisms (6 papers). Marcus Keatinge is often cited by papers focused on Zebrafish Biomedical Research Applications (13 papers), Neuroinflammation and Neurodegeneration Mechanisms (7 papers) and Neurogenesis and neuroplasticity mechanisms (6 papers). Marcus Keatinge collaborates with scholars based in United Kingdom, United States and Germany. Marcus Keatinge's co-authors include Oliver Bandmann, Catherina G. Becker, Themistoklis M. Tsarouchas, Thomas Becker, Daniel Wehner, Leonardo Cavone, Smijin Soman, Jacek Kuźnicki, Yi Feng and Nikolay V. Ogryzko and has published in prestigious journals such as Nature Communications, Journal of Neuroscience and Nature Neuroscience.

In The Last Decade

Marcus Keatinge

22 papers receiving 951 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Marcus Keatinge United Kingdom 12 428 240 207 202 193 22 953
Naohiro Egawa Japan 14 350 0.8× 132 0.6× 236 1.1× 159 0.8× 175 0.9× 35 819
An‐Chi Tien United States 15 751 1.8× 231 1.0× 177 0.9× 223 1.1× 62 0.3× 40 1.3k
Inge Van Hove Belgium 22 596 1.4× 134 0.6× 295 1.4× 305 1.5× 70 0.4× 38 1.4k
Hiroko Ikeshima‐Kataoka Japan 15 554 1.3× 187 0.8× 244 1.2× 254 1.3× 90 0.5× 24 956
Janos Groh Germany 22 311 0.7× 132 0.6× 356 1.7× 476 2.4× 327 1.7× 38 1.1k
Benjamin L.L. Clayton United States 13 597 1.4× 162 0.7× 180 0.9× 158 0.8× 53 0.3× 18 951
Bingyin Su China 16 269 0.6× 92 0.4× 196 0.9× 134 0.7× 204 1.1× 42 794
Yevgeniya A. Mironova United States 14 378 0.9× 240 1.0× 220 1.1× 549 2.7× 125 0.6× 17 1.1k
Ryan Insolera United States 13 594 1.4× 238 1.0× 179 0.9× 319 1.6× 63 0.3× 14 1.1k
Raul Krauss United States 11 520 1.2× 136 0.6× 102 0.5× 349 1.7× 109 0.6× 14 1.0k

Countries citing papers authored by Marcus Keatinge

Since Specialization
Citations

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

Fields of papers citing papers by Marcus Keatinge

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Marcus Keatinge

This figure shows the co-authorship network connecting the top 25 collaborators of Marcus Keatinge. A scholar is included among the top collaborators of Marcus Keatinge 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 Marcus Keatinge. Marcus Keatinge 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
1.
Keatinge, Marcus, Oliver Pearce, Petteri Piepponen, et al.. (2025). A zebrafish model of acmsd deficiency does not support a prominent role for ACMSD in Parkinson’s disease. npj Parkinson s Disease. 11(1). 118–118. 2 indexed citations
2.
Mi, Xuelong, Daniel Soong, Jenea M. Bin, et al.. (2025). Activity-driven myelin sheath growth is mediated by mGluR5. Nature Neuroscience. 28(6). 1213–1225. 1 indexed citations
3.
Tsarouchas, Themistoklis M., Catherina G. Becker, Thomas Becker, et al.. (2024). C9ORF72 Deficiency Results in Neurodegeneration in the Zebrafish Retina. Journal of Neuroscience. 44(25). e2128232024–e2128232024. 1 indexed citations
4.
Keatinge, Marcus, et al.. (2023). Rapid Testing of Gene Function in Axonal Regeneration After Spinal Cord Injury Using Larval Zebrafish. Methods in molecular biology. 2636. 263–277. 1 indexed citations
5.
Keatinge, Marcus, Matthew E. Gegg, Lisa Watson, et al.. (2023). Unexpected phenotypic and molecular changes of combined glucocerebrosidase and acid sphingomyelinase deficiency. Disease Models & Mechanisms. 16(6). 3 indexed citations
6.
García‐González, Judit, et al.. (2022). Ankk1 Loss of Function Disrupts Dopaminergic Pathways in Zebrafish. Frontiers in Neuroscience. 16. 794653–794653. 5 indexed citations
7.
Cavone, Leonardo, Ana‐Maria Oprişoreanu, Elisa Pedersen, et al.. (2021). A unique macrophage subpopulation signals directly to progenitor cells to promote regenerative neurogenesis in the zebrafish spinal cord. Developmental Cell. 56(11). 1617–1630.e6. 57 indexed citations
8.
Keatinge, Marcus, Themistoklis M. Tsarouchas, Davide Gianni, et al.. (2021). CRISPR gRNA phenotypic screening in zebrafish reveals pro-regenerative genes in spinal cord injury. PLoS Genetics. 17(4). e1009515–e1009515. 42 indexed citations
9.
Brown, Sarah, Ibrahim Boussaad, Javier Jarazo, et al.. (2021). PINK1 deficiency impairs adult neurogenesis of dopaminergic neurons. Scientific Reports. 11(1). 6617–6617. 26 indexed citations
10.
11.
Cavone, Leonardo, Ana‐Maria Oprişoreanu, Elisa Pedersen, et al.. (2020). A Unique Macrophage Subpopulation Signals Directly to Progenitor Cells to Promote Regenerative Neurogenesis in the Zebrafish Spinal Cord. SSRN Electronic Journal. 5 indexed citations
12.
13.
Watson, Lisa, Marcus Keatinge, Matthew E. Gegg, et al.. (2019). Ablation of the pro-inflammatory master regulator miR-155 does not mitigate neuroinflammation or neurodegeneration in a vertebrate model of Gaucher's disease. Neurobiology of Disease. 127. 563–569. 18 indexed citations
14.
15.
Herzog, Chiara, et al.. (2019). Rapid clearance of cellular debris by microglia limits secondary neuronal cell death after brain injury in vivo. Development. 146(9). 80 indexed citations
16.
Schöndorf, David C., Dina Ivanyuk, Pascale Baden, et al.. (2018). The NAD+ Precursor Nicotinamide Riboside Rescues Mitochondrial Defects and Neuronal Loss in iPSC and Fly Models of Parkinson’s Disease. Cell Reports. 23(10). 2976–2988. 243 indexed citations
17.
Tsarouchas, Themistoklis M., Daniel Wehner, Leonardo Cavone, et al.. (2018). Dynamic control of proinflammatory cytokines Il-1β and Tnf-α by macrophages in zebrafish spinal cord regeneration. Nature Communications. 9(1). 4670–4670. 214 indexed citations
18.
Baker, David, D. Blackburn, Marcus Keatinge, et al.. (2015). Lysosomal and phagocytic activity is increased in astrocytes during disease progression in the SOD1 G93A mouse model of amyotrophic lateral sclerosis. Frontiers in Cellular Neuroscience. 9. 410–410. 40 indexed citations
19.
Payne, Thomas, Marcus Keatinge, Marc Da Costa, & Oliver Bandmann. (2015). MPP+ IN A ZEBRAFISH MODEL OF GLUCOCEREBROSIDASE 1 DEFICIENCY. Journal of Neurology Neurosurgery & Psychiatry. 86(11). e4.93–e4. 1 indexed citations
20.
Flinn, Laura, Marcus Keatinge, Sandrine Bretaud, et al.. (2013). TigarB causes mitochondrial dysfunction and neuronal loss in PINK1 deficiency. Annals of Neurology. 74(6). 837–847. 69 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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