Markus Kipp

8.9k total citations
160 papers, 6.7k citations indexed

About

Markus Kipp is a scholar working on Neurology, Pathology and Forensic Medicine and Developmental Neuroscience. According to data from OpenAlex, Markus Kipp has authored 160 papers receiving a total of 6.7k indexed citations (citations by other indexed papers that have themselves been cited), including 78 papers in Neurology, 65 papers in Pathology and Forensic Medicine and 61 papers in Developmental Neuroscience. Recurrent topics in Markus Kipp's work include Neuroinflammation and Neurodegeneration Mechanisms (72 papers), Multiple Sclerosis Research Studies (64 papers) and Neurogenesis and neuroplasticity mechanisms (59 papers). Markus Kipp is often cited by papers focused on Neuroinflammation and Neurodegeneration Mechanisms (72 papers), Multiple Sclerosis Research Studies (64 papers) and Neurogenesis and neuroplasticity mechanisms (59 papers). Markus Kipp collaborates with scholars based in Germany, Netherlands and United Kingdom. Markus Kipp's co-authors include Cordian Beyer, Tim Clarner, Sandra Amor, Jon Dang, Paul van der Valk, Klaus Tenbrock, Kim Ohl, Sonja Johann, Adib Zendedel and Tanja Hochstrasser and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Journal of Neuroscience and SHILAP Revista de lepidopterología.

In The Last Decade

Markus Kipp

159 papers receiving 6.6k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Markus Kipp Germany 45 2.9k 2.2k 2.1k 2.0k 1.3k 160 6.7k
Ranjan Dutta United States 30 2.7k 0.9× 2.2k 1.0× 1.2k 0.6× 1.8k 0.9× 1.5k 1.1× 80 6.3k
Anna Williams United Kingdom 41 2.8k 1.0× 2.2k 1.0× 2.6k 1.2× 1.5k 0.7× 1.3k 1.0× 113 7.1k
John R. Bethea United States 45 1.9k 0.6× 1.8k 0.8× 886 0.4× 2.4k 1.2× 1.3k 1.0× 105 7.1k
Jack van Horssen Netherlands 58 3.4k 1.2× 4.2k 1.9× 980 0.5× 2.8k 1.4× 2.0k 1.5× 116 10.2k
Roberta Brambilla United States 38 1.6k 0.6× 1.6k 0.8× 547 0.3× 767 0.4× 874 0.7× 94 4.8k
Bogdan A. Stoica United States 56 2.4k 0.8× 4.4k 2.0× 941 0.5× 1.1k 0.6× 1.2k 0.9× 113 9.4k
Stella E. Tsirka United States 53 3.3k 1.2× 3.3k 1.5× 1.1k 0.5× 449 0.2× 1.6k 1.2× 145 10.0k
Marı́a Domercq Spain 35 2.4k 0.8× 1.6k 0.7× 929 0.4× 493 0.2× 566 0.4× 55 5.7k
Bart J. L. Eggen Netherlands 46 3.8k 1.3× 2.3k 1.0× 984 0.5× 373 0.2× 2.3k 1.8× 144 7.5k
Hideyuki Takeuchi Japan 48 3.1k 1.1× 2.4k 1.1× 621 0.3× 613 0.3× 1.7k 1.3× 160 7.7k

Countries citing papers authored by Markus Kipp

Since Specialization
Citations

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

Fields of papers citing papers by Markus Kipp

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Markus Kipp

This figure shows the co-authorship network connecting the top 25 collaborators of Markus Kipp. A scholar is included among the top collaborators of Markus Kipp 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 Markus Kipp. Markus Kipp 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.
Krüger, Jürgen, et al.. (2025). Siponimod supports remyelination in the non-supportive environment. Scientific Reports. 15(1). 4216–4216. 1 indexed citations
2.
Krüger, Jürgen, et al.. (2024). Titration of cuprizone induces reliable demyelination. Brain Research. 1850. 149410–149410. 1 indexed citations
3.
Kipp, Markus. (2024). From GPT-3.5 to GPT-4.o: A Leap in AI’s Medical Exam Performance. Information. 15(9). 543–543. 13 indexed citations
4.
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6.
Kipp, Markus, et al.. (2023). The Cuprizone Mouse Model: A Comparative Study of Cuprizone Formulations from Different Manufacturers. International Journal of Molecular Sciences. 24(13). 10564–10564. 5 indexed citations
7.
Lindsay, Susan L., Jiangshan Zhan, Miriam Scheld, et al.. (2023). Low sulfated heparan sulfate mimetic differentially affects repair in immune‐mediated and toxin‐induced experimental models of demyelination. Glia. 71(7). 1683–1698. 2 indexed citations
8.
Schuster, Katharina, et al.. (2023). Establishment of a Murine Chronic Anorexia Nervosa Model. Cells. 12(13). 1710–1710. 5 indexed citations
9.
Wilk, Aleksandra, et al.. (2023). Current Status Regarding Immunosuppressive Treatment in Patients after Renal Transplantation. International Journal of Molecular Sciences. 24(12). 10301–10301. 35 indexed citations
10.
Noort, Johannes M. van, David Baker, Markus Kipp, & Sandra Amor. (2023). The pathogenesis of multiple sclerosis: a series of unfortunate events. Clinical & Experimental Immunology. 214(1). 1–17. 9 indexed citations
11.
Frintrop, Linda, Jens Kurth, Bernd J. Krause, et al.. (2022). Siponimod ameliorates metabolic oligodendrocyte injury via the sphingosine-1 phosphate receptor 5. Proceedings of the National Academy of Sciences. 119(40). e2204509119–e2204509119. 17 indexed citations
12.
Dhanasingh, Anandhan, M. Schulze, Markus Kipp, et al.. (2021). CT imaging-based approaches to cochlear duct length estimation—a human temporal bone study. European Radiology. 32(2). 1014–1023. 22 indexed citations
13.
Schmitz, Christoph, et al.. (2019). Animal Weight Is an Important Variable for Reliable Cuprizone-Induced Demyelination. Journal of Molecular Neuroscience. 68(4). 522–528. 13 indexed citations
14.
Scheld, Miriam, Athanassios Fragoulis, Stella Nyamoya, et al.. (2018). Mitochondrial Impairment in Oligodendroglial Cells Induces Cytokine Expression and Signaling. Journal of Molecular Neuroscience. 67(2). 265–275. 13 indexed citations
15.
Trépanier, Marc‐Olivier, et al.. (2018). Phosphatidylcholine 36:1 concentration decreases along with demyelination in the cuprizone animal model and in post‐mortem multiple sclerosis brain tissue. Journal of Neurochemistry. 145(6). 504–515. 19 indexed citations
16.
Hochstrasser, Tanja, et al.. (2018). Do pre-clinical multiple sclerosis models allow us to measure neurodegeneration and clinical progression?. Expert Review of Neurotherapeutics. 18(5). 351–353. 9 indexed citations
17.
Hochstrasser, Tanja, et al.. (2016). Acute axonal damage in three different murine models of multiple sclerosis. Multiple Sclerosis Journal. 22. 400. 4 indexed citations
18.
Scheld, Miriam, Kim Ohl, Klaus Tenbrock, et al.. (2016). Neurodegeneration Triggers Peripheral Immune Cell Recruitment into the Forebrain. Journal of Neuroscience. 36(4). 1410–1415. 62 indexed citations
19.
Puentes, Fabìola, Markus Kipp, Cordian Beyer, et al.. (2013). Characterization of immune response to neurofilament light in experimental autoimmune encephalomyelitis. Journal of Neuroinflammation. 10(1). 118–118. 9 indexed citations
20.
Dang, Jon, Lars‐Ove Brandenburg, Christian Rosén, et al.. (2011). Nrf2 Expression by Neurons, Astroglia, and Microglia in the Cerebral Cortical Penumbra of Ischemic Rats. Journal of Molecular Neuroscience. 46(3). 578–584. 51 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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