Rupert Derler

784 total citations · 1 hit paper
9 papers, 571 citations indexed

About

Rupert Derler is a scholar working on Cell Biology, Molecular Biology and Oncology. According to data from OpenAlex, Rupert Derler has authored 9 papers receiving a total of 571 indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Cell Biology, 4 papers in Molecular Biology and 4 papers in Oncology. Recurrent topics in Rupert Derler's work include Proteoglycans and glycosaminoglycans research (5 papers), Glycosylation and Glycoproteins Research (4 papers) and Chemokine receptors and signaling (4 papers). Rupert Derler is often cited by papers focused on Proteoglycans and glycosaminoglycans research (5 papers), Glycosylation and Glycoproteins Research (4 papers) and Chemokine receptors and signaling (4 papers). Rupert Derler collaborates with scholars based in Austria, United Kingdom and Germany. Rupert Derler's co-authors include Martha Gschwandtner, Kim S. Midwood, Andreas J. Kungl, Bernd Gesslbauer, Michael Lichtenauer, Thomas K. Felder, Peter Jirak, Kristen Kopp, Richard Rezar and Uta C. Hoppe and has published in prestigious journals such as International Journal of Molecular Sciences, Methods in enzymology on CD-ROM/Methods in enzymology and Frontiers in Immunology.

In The Last Decade

Rupert Derler

9 papers receiving 565 citations

Hit Papers

More Than Just Attractive... 2019 2026 2021 2023 2019 100 200 300 400

Author Peers

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

Author Last Decade Papers Cites
Rupert Derler 226 175 104 62 56 9 571
Martha Gschwandtner 283 1.3× 204 1.2× 163 1.6× 67 1.1× 55 1.0× 13 693
Jiayou Tang 215 1.0× 215 1.2× 70 0.7× 66 1.1× 64 1.1× 37 591
Nathalie Burg 183 0.8× 360 2.1× 78 0.8× 44 0.7× 52 0.9× 10 706
Kun Shi 176 0.8× 289 1.7× 81 0.8× 42 0.7× 75 1.3× 35 713
Roland Immler 302 1.3× 187 1.1× 55 0.5× 50 0.8× 37 0.7× 23 629
Serena Tedesco 252 1.1× 219 1.3× 65 0.6× 69 1.1× 58 1.0× 13 618
Luiz G. Almeida 125 0.6× 223 1.3× 93 0.9× 65 1.0× 32 0.6× 13 609
Facundo Pelorosso 321 1.4× 253 1.4× 100 1.0× 72 1.2× 68 1.2× 22 876
Huiting Su 240 1.1× 195 1.1× 122 1.2× 95 1.5× 89 1.6× 24 589
Jun Tan 244 1.1× 332 1.9× 63 0.6× 78 1.3× 39 0.7× 33 800

Countries citing papers authored by Rupert Derler

Since Specialization
Citations

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

Fields of papers citing papers by Rupert Derler

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Rupert Derler

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

All Works

9 of 9 papers shown
1.
Fisher, Krishna J., Rupert Derler, Florian Sonntag, et al.. (2025). Polo-like kinase inhibitors increase AAV production by halting cell cycle progression. Molecular Therapy — Methods & Clinical Development. 33(1). 101412–101412. 1 indexed citations
2.
Gschwandtner, Martha, Claire Deligne, Thomas Loustau, et al.. (2023). Investigating Chemokine-Matrix Networks in Breast Cancer: Tenascin-C Sets the Tone for CCL2. International Journal of Molecular Sciences. 24(9). 8365–8365. 3 indexed citations
3.
Derler, Rupert, et al.. (2021). Isolation and Characterization of Heparan Sulfate from Human Lung Tissues. Molecules. 26(18). 5512–5512. 3 indexed citations
4.
Rezar, Richard, Peter Jirak, Martha Gschwandtner, et al.. (2020). Heart-Type Fatty Acid-Binding Protein (H-FABP) and Its Role as a Biomarker in Heart Failure: What Do We Know So Far?. Journal of Clinical Medicine. 9(1). 164–164. 73 indexed citations
5.
Gschwandtner, Martha, Rupert Derler, & Kim S. Midwood. (2019). More Than Just Attractive: How CCL2 Influences Myeloid Cell Behavior Beyond Chemotaxis. Frontiers in Immunology. 10. 2759–2759. 442 indexed citations breakdown →
6.
Derler, Rupert, et al.. (2018). Molecular dynamics simulations of the chemokine CCL2 in complex with pull down-derived heparan sulfate hexasaccharides. Biochimica et Biophysica Acta (BBA) - General Subjects. 1863(3). 528–533. 6 indexed citations
7.
Derler, Rupert, et al.. (2017). Glycosaminoglycan-Mediated Downstream Signaling of CXCL8 Binding to Endothelial Cells. International Journal of Molecular Sciences. 18(12). 2605–2605. 22 indexed citations
8.
Gesslbauer, Bernd, et al.. (2016). Exploring the glycosaminoglycan–protein interaction network by glycan‐mediated pull‐down proteomics. Electrophoresis. 37(11). 1437–1447. 18 indexed citations
9.
Gschwandtner, Martha, et al.. (2015). Preparation and Characterization of Glycosaminoglycan Chemokine Coreceptors. Methods in enzymology on CD-ROM/Methods in enzymology. 570. 517–538. 3 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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