Jan Gettemans

6.8k total citations
94 papers, 3.3k citations indexed

About

Jan Gettemans is a scholar working on Molecular Biology, Cell Biology and Radiology, Nuclear Medicine and Imaging. According to data from OpenAlex, Jan Gettemans has authored 94 papers receiving a total of 3.3k indexed citations (citations by other indexed papers that have themselves been cited), including 60 papers in Molecular Biology, 44 papers in Cell Biology and 29 papers in Radiology, Nuclear Medicine and Imaging. Recurrent topics in Jan Gettemans's work include Monoclonal and Polyclonal Antibodies Research (28 papers), Cellular Mechanics and Interactions (25 papers) and Slime Mold and Myxomycetes Research (14 papers). Jan Gettemans is often cited by papers focused on Monoclonal and Polyclonal Antibodies Research (28 papers), Cellular Mechanics and Interactions (25 papers) and Slime Mold and Myxomycetes Research (14 papers). Jan Gettemans collaborates with scholars based in Belgium, United States and United Kingdom. Jan Gettemans's co-authors include Joël Vandekerckhove, Joël Vandekerckhove, Veerle De Corte, Isabel Van Audenhove, Ciska Boucherie, Erik Bruyneel, Kris Meerschaert, Katrien Van Impe, Olivier Zwaenepoel and Berlinda Vanloo and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Nucleic Acids Research and Journal of Biological Chemistry.

In The Last Decade

Jan Gettemans

91 papers receiving 3.3k citations

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author Last Decade Papers Cites
Jan Gettemans 2.1k 1.2k 637 333 319 94 3.3k
Karl‐Johan Leuchowius 2.3k 1.1× 616 0.5× 239 0.4× 363 1.1× 394 1.2× 15 3.2k
Menachem Katz 2.4k 1.1× 1.0k 0.8× 254 0.4× 339 1.0× 865 2.7× 18 3.5k
Richard A. Kammerer 3.5k 1.7× 1.5k 1.2× 274 0.4× 308 0.9× 271 0.8× 101 5.2k
Jonas Jarvius 3.3k 1.6× 670 0.5× 316 0.5× 295 0.9× 335 1.1× 23 4.3k
Letizia Lanzetti 2.2k 1.0× 1.4k 1.1× 166 0.3× 362 1.1× 658 2.1× 39 3.6k
Lee K. Opresko 1.9k 0.9× 518 0.4× 979 1.5× 262 0.8× 911 2.9× 46 3.1k
Frédéric Bard 2.9k 1.4× 1.4k 1.1× 131 0.2× 601 1.8× 398 1.2× 56 3.9k
Peter J. Schatz 3.3k 1.6× 1.1k 0.9× 867 1.4× 476 1.4× 286 0.9× 56 4.8k
Shuji Akiyama 1.6k 0.8× 712 0.6× 181 0.3× 271 0.8× 123 0.4× 58 2.9k
Shoko Nishihara 2.8k 1.3× 598 0.5× 385 0.6× 990 3.0× 330 1.0× 136 3.8k

Countries citing papers authored by Jan Gettemans

Since Specialization
Citations

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

Fields of papers citing papers by Jan Gettemans

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jan Gettemans

This figure shows the co-authorship network connecting the top 25 collaborators of Jan Gettemans. A scholar is included among the top collaborators of Jan Gettemans 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 Jan Gettemans. Jan Gettemans 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.
Zwaenepoel, Olivier, et al.. (2025). Highly sensitive nanobody-immunosensor for macrophage-capping protein. Biosensors and Bioelectronics. 287. 117681–117681. 1 indexed citations
2.
Zwaenepoel, Olivier, et al.. (2024). Development of nanobodies against the coat protein of maize chlorotic mottle virus. FEBS Open Bio. 14(10). 1746–1757. 1 indexed citations
3.
Rossignoli, Filippo, et al.. (2024). Allogeneic stem cells engineered to release interferon β and scFv-PD1 target glioblastoma and alter the tumor microenvironment. Cytotherapy. 26(10). 1217–1226. 1 indexed citations
4.
Zwaenepoel, Olivier, et al.. (2023). Nanobodies: a promising tool to perturb ApoE4 activity in Alzheimer’s disease pathology. Alzheimer s & Dementia. 19(S13). 2 indexed citations
5.
Lawson, Campbell D., S Peel, Asier Jayo, et al.. (2022). Nuclear fascin regulates cancer cell survival. eLife. 11. 9 indexed citations
6.
Wang, Feng, Yuanyuan Yang, Debin Wan, et al.. (2022). Nanobodies for accurate recognition of iso-tenuazonic acid and development of sensitive immunoassay for contaminant detection in foods. Food Control. 136. 108835–108835. 14 indexed citations
7.
8.
Giorgino, Toni, Mario Milani, Eloise Mastrangelo, et al.. (2019). Nanobody interaction unveils structure, dynamics and proteotoxicity of the Finnish-type amyloidogenic gelsolin variant. Biochimica et Biophysica Acta (BBA) - Molecular Basis of Disease. 1865(3). 648–660. 19 indexed citations
9.
Gettemans, Jan, et al.. (2018). Cortactin and fascin-1 regulate extracellular vesicle release by controlling endosomal trafficking or invadopodia formation and function. Scientific Reports. 8(1). 15606–15606. 45 indexed citations
10.
Audenhove, Isabel Van, Nincy Debeuf, Ciska Boucherie, & Jan Gettemans. (2015). Fascin actin bundling controls podosome turnover and disassembly while cortactin is involved in podosome assembly by its SH3 domain in THP-1 macrophages and dendritic cells. Biochimica et Biophysica Acta (BBA) - Molecular Cell Research. 1853(5). 940–952. 33 indexed citations
11.
Wongsantichon, Jantana, Inge Everaert, Olivier Zwaenepoel, et al.. (2015). An ER-directed gelsolin nanobody targets the first step in amyloid formation in a gelsolin amyloidosis mouse model. Human Molecular Genetics. 24(9). 2492–2507. 33 indexed citations
12.
Everaert, Inge, Olivier Zwaenepoel, Joël Vandekerckhove, et al.. (2014). Chaperone Nanobodies Protect Gelsolin Against MT1-MMP Degradation and Alleviate Amyloid Burden in the Gelsolin Amyloidosis Mouse Model. Molecular Therapy. 22(10). 1768–1778. 29 indexed citations
13.
Impe, Katrien Van, et al.. (2009). The actin-capping protein CapG localizes to microtubule-dependent organelles during the cell cycle. Biochemical and Biophysical Research Communications. 380(1). 166–170. 25 indexed citations
14.
Corte, Veerle De, et al.. (2008). Multiple isoforms of the tumor suppressor myopodin are simultaneously transcribed in cancer cells. Biochemical and Biophysical Research Communications. 370(2). 269–273. 11 indexed citations
15.
Vandekerckhove, Joël, et al.. (2005). Plastins: versatile modulators of actin organization in (patho)physiological cellular processes. Acta Pharmacologica Sinica. 26(7). 769–779. 135 indexed citations
16.
Impe, Katrien Van, Veerle De Corte, Erik Bruyneel, et al.. (2005). Molecular Basis for Dissimilar Nuclear Trafficking of the Actin‐Bundling Protein Isoforms T‐ and L‐Plastin. Traffic. 6(4). 335–345. 14 indexed citations
17.
Preisinger, Christian, Benjamin Short, Veerle De Corte, et al.. (2004). YSK1 is activated by the Golgi matrix protein GM130 and plays a role in cell migration through its substrate 14-3-3ζ. The Journal of Cell Biology. 164(7). 1009–1020. 221 indexed citations
18.
Zimmermann, Pascale, Kris Meerschaert, Gunter Reekmans, et al.. (2002). PIP2-PDZ Domain Binding Controls the Association of Syntenin with the Plasma Membrane. Molecular Cell. 9(6). 1215–1225. 164 indexed citations
19.
20.
Waelkens, Etienne, et al.. (1995). The Actin-binding Properties of the Physarum Actin-Fragmin Complex. Journal of Biological Chemistry. 270(6). 2644–2651. 33 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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