Sven Geisler

4.0k total citations · 1 hit paper
14 papers, 3.2k citations indexed

About

Sven Geisler is a scholar working on Molecular Biology, Neurology and Epidemiology. According to data from OpenAlex, Sven Geisler has authored 14 papers receiving a total of 3.2k indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Molecular Biology, 7 papers in Neurology and 7 papers in Epidemiology. Recurrent topics in Sven Geisler's work include Autophagy in Disease and Therapy (7 papers), Parkinson's Disease Mechanisms and Treatments (6 papers) and Ubiquitin and proteasome pathways (4 papers). Sven Geisler is often cited by papers focused on Autophagy in Disease and Therapy (7 papers), Parkinson's Disease Mechanisms and Treatments (6 papers) and Ubiquitin and proteasome pathways (4 papers). Sven Geisler collaborates with scholars based in Germany, Japan and United States. Sven Geisler's co-authors include Philipp J. Kahle, Fabienne C. Fiesel, Wolfdieter Springer, Kira M. Holmström, Oliver C. Rothfuss, Stephanie Weber, Sonia Golombek, Markus A. Queisser, Klaus T. Preissner and Jacqueline Wettengel and has published in prestigious journals such as Nucleic Acids Research, Journal of Biological Chemistry and The Journal of Immunology.

In The Last Decade

Sven Geisler

13 papers receiving 3.2k citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

PINK1/Parkin-mediated mitophagy is dependent on VDAC1 and p62/SQSTM1

2010 2.3k citations Sven Geisler, Kira M. Holmström et al. Nature Cell Biology profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Sven Geisler Germany	11	1.9k	1.9k	976	610	504	14	3.2k
Sumihiro Kawajiri Japan	12	2.0k 1.1×	1.6k 0.9×	828 0.8×	545 0.9×	361 0.7×	21	3.2k
Oliver C. Rothfuss Germany	16	2.0k 1.1×	1.6k 0.9×	766 0.8×	510 0.8×	368 0.7×	18	3.5k
Fumika Koyano Japan	14	1.7k 0.9×	1.8k 0.9×	905 0.9×	423 0.7×	383 0.8×	18	2.7k
Kei Okatsu Japan	16	2.8k 1.5×	2.9k 1.6×	1.5k 1.5×	727 1.2×	614 1.2×	27	4.4k
Sarah Pickles Canada	10	1.6k 0.9×	920 0.5×	609 0.6×	381 0.6×	275 0.5×	16	2.5k
Seok Min Jin United States	12	3.4k 1.8×	3.0k 1.6×	1.5k 1.6×	1.1k 1.8×	686 1.4×	12	5.3k
Thomas G. McWilliams United Kingdom	16	1.1k 0.6×	1.1k 0.6×	411 0.4×	371 0.6×	274 0.5×	28	2.0k
Guy Las United States	14	2.7k 1.5×	1.4k 0.7×	259 0.3×	886 1.5×	395 0.8×	17	3.6k
Ashish C. Massey United States	15	1.1k 0.6×	2.1k 1.1×	814 0.8×	1.1k 1.8×	1.1k 2.3×	21	3.3k
Urmi Bandyopadhyay United States	13	830 0.4×	1.3k 0.7×	309 0.3×	653 1.1×	682 1.4×	18	2.2k

Countries citing papers authored by Sven Geisler

Since Specialization

Citations

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

Fields of papers citing papers by Sven Geisler

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Sven Geisler

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

All Works

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14 of 14 papers shown

Assmann, Julian C., Helge Müller‐Fielitz, Kristian Händler, et al.. (2025). Diet modulates the therapeutic effects of dimethyl fumarate mediated by the immunometabolic neutrophil receptor HCAR2. eLife. 14. 2 indexed citations

Friščić, Jasna, Sven Geisler, Rebecca Lee, et al.. (2025). Compstatins abolish pathogenic fibroblast function associated with inflammatory maladaptation of tissues. Immunobiology. 230(4). 153005–153005.

Nording, Henry, Manuela Sauter, Sven Geisler, et al.. (2022). Activated Platelets Upregulate β2 Integrin Mac-1 (CD11b/CD18) on Dendritic Cells, Which Mediates Heterotypic Cell–Cell Interaction. The Journal of Immunology. 208(7). 1729–1741. 10 indexed citations

Nalpas, Nicolas, et al.. (2021). Temporal Analysis of Protein Ubiquitylation and Phosphorylation During Parkin-Dependent Mitophagy. Molecular & Cellular Proteomics. 21(2). 100191–100191. 13 indexed citations

Geisler, Sven, Sonia Golombek, Etsuro Nakanishi, et al.. (2019). Ubiquitin-specific protease USP36 knockdown impairs Parkin-dependent mitophagy via downregulation of Beclin-1-associated autophagy-related ATG14L. Experimental Cell Research. 384(2). 111641–111641. 25 indexed citations

Wettengel, Jacqueline, Philipp Reautschnig, Sven Geisler, Philipp J. Kahle, & Thorsten Stafforst. (2016). Harnessing human ADAR2 for RNA repair – Recoding a PINK1 mutation rescues mitophagy. Nucleic Acids Research. 45(5). gkw911–gkw911. 97 indexed citations

Sugeno, Naoto, Takafumi Hasegawa, Nobuyuki Tanaka, et al.. (2014). Lys-63-linked Ubiquitination by E3 Ubiquitin Ligase Nedd4-1 Facilitates Endosomal Sequestration of Internalized α-Synuclein. Journal of Biological Chemistry. 289(26). 18137–18151. 58 indexed citations

Miura, Emiko, Takafumi Hasegawa, Masatoshi Konno, et al.. (2014). VPS35 dysfunction impairs lysosomal degradation of α-synuclein and exacerbates neurotoxicity in a Drosophila model of Parkinson's disease. Neurobiology of Disease. 71. 1–13. 152 indexed citations

Hans, Friederike, Fabienne C. Fiesel, Tobias M. Rasse, et al.. (2014). UBE2E Ubiquitin-conjugating Enzymes and Ubiquitin Isopeptidase Y Regulate TDP-43 Protein Ubiquitination. Journal of Biological Chemistry. 289(27). 19164–19179. 70 indexed citations

10.

Geisler, Sven, et al.. (2014). UBE2N, UBE2L3 and UBE2D2/3 ubiquitin-conjugating enzymes are essential for parkin-dependent mitophagy. Journal of Cell Science. 127(Pt 15). 3280–93. 77 indexed citations

11.

Geisler, Sven, Kira M. Holmström, Fabienne C. Fiesel, et al.. (2010). PINK1/Parkin-mediated mitophagy is dependent on VDAC1 and p62/SQSTM1. Nature Cell Biology. 12(2). 119–131. 2297 indexed citations breakdown →

12.

Geisler, Sven, Kira M. Holmström, Stephanie Weber, et al.. (2010). The PINK1/Parkin-mediated mitophagy is compromised by PD-associated mutations. Autophagy. 6(7). 871–878. 247 indexed citations

13.

Solovyova, Alexandra S., et al.. (2009). Physical and functional interactions between Escherichia coli MutL and the Vsr repair endonuclease. Nucleic Acids Research. 37(13). 4453–4463. 21 indexed citations

14.

Queisser, Markus A., Dachun Yao, Sven Geisler, et al.. (2009). Hyperglycemia Impairs Proteasome Function by Methylglyoxal. Diabetes. 59(3). 670–678. 153 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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