Uwe Marx

6.5k total citations · 1 hit paper
125 papers, 4.9k citations indexed

About

Uwe Marx is a scholar working on Biomedical Engineering, Molecular Biology and Oncology. According to data from OpenAlex, Uwe Marx has authored 125 papers receiving a total of 4.9k indexed citations (citations by other indexed papers that have themselves been cited), including 68 papers in Biomedical Engineering, 48 papers in Molecular Biology and 16 papers in Oncology. Recurrent topics in Uwe Marx's work include 3D Printing in Biomedical Research (61 papers), Innovative Microfluidic and Catalytic Techniques Innovation (22 papers) and Monoclonal and Polyclonal Antibodies Research (15 papers). Uwe Marx is often cited by papers focused on 3D Printing in Biomedical Research (61 papers), Innovative Microfluidic and Catalytic Techniques Innovation (22 papers) and Monoclonal and Polyclonal Antibodies Research (15 papers). Uwe Marx collaborates with scholars based in Germany, United States and United Kingdom. Uwe Marx's co-authors include Roland Lauster, Frank Sonntag, Alexander Tonevitsky, Ilka Maschmeyer, Alexandra Lorenz, Tobias Hasenberg, Eva-Maria Materne, Katharina Schimek, G Lindner and Reyk Horland and has published in prestigious journals such as SHILAP Revista de lepidopterología, Nature Biotechnology and Biomaterials.

In The Last Decade

Uwe Marx

121 papers receiving 4.8k citations

Hit Papers

A four-organ-chip for interconnected long-term co-culture... 2015 2026 2018 2022 2015 200 400 600

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Uwe Marx Germany 37 3.3k 1.5k 629 552 417 125 4.9k
Mandy B. Esch United States 25 2.5k 0.8× 1.0k 0.7× 535 0.9× 449 0.8× 335 0.8× 43 4.2k
Hasan Erbil Abaci United States 18 1.7k 0.5× 1.0k 0.7× 414 0.7× 389 0.7× 305 0.7× 33 3.5k
Jong Hwan Sung South Korea 40 3.7k 1.1× 1.3k 0.8× 644 1.0× 507 0.9× 409 1.0× 110 5.1k
Catarina Brito Portugal 31 1.6k 0.5× 1.6k 1.1× 232 0.4× 758 1.4× 502 1.2× 97 3.6k
Paul Vulto Netherlands 33 3.0k 0.9× 1.1k 0.7× 562 0.9× 550 1.0× 240 0.6× 75 3.9k
M. Fátima Leite Brazil 36 750 0.2× 2.0k 1.3× 312 0.5× 326 0.6× 901 2.2× 108 4.2k
Yasuyuki Sakai Japan 32 2.8k 0.8× 1.7k 1.1× 307 0.5× 360 0.7× 1.3k 3.1× 238 5.2k
Peter Ertl Austria 38 2.6k 0.8× 900 0.6× 431 0.7× 207 0.4× 251 0.6× 135 3.7k
Kyung‐Jin Jang South Korea 18 1.8k 0.5× 815 0.6× 312 0.5× 275 0.5× 301 0.7× 31 2.6k
Dawidson Assis Gomes Brazil 36 433 0.1× 1.7k 1.2× 237 0.4× 419 0.8× 508 1.2× 134 3.8k

Countries citing papers authored by Uwe Marx

Since Specialization
Citations

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

Fields of papers citing papers by Uwe Marx

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Uwe Marx

This figure shows the co-authorship network connecting the top 25 collaborators of Uwe Marx. A scholar is included among the top collaborators of Uwe Marx 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 Uwe Marx. Uwe Marx 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.
Thon, Maria, et al.. (2025). Differential biomarker expression of blood and lymphatic vasculature in multi-organ-chips. Scientific Reports. 15(1). 14492–14492. 1 indexed citations
3.
Maschmeyer, Ilka, Edward L. LeCluyse, Camille Géniès, et al.. (2023). Development of a microphysiological skin-liver-thyroid Chip3 model and its application to evaluate the effects on thyroid hormones of topically applied cosmetic ingredients under consumer-relevant conditions. Frontiers in Pharmacology. 14. 1076254–1076254. 15 indexed citations
4.
Ramme, Anja Patricia, Anna Gerhartl, Andreas Brachner, et al.. (2022). A Human Stem Cell-Derived Brain-Liver Chip for Assessing Blood-Brain-Barrier Permeation of Pharmaceutical Drugs. Cells. 11(20). 3295–3295. 25 indexed citations
5.
Thon, Maria, Lenie J. van den Broek, Sander W. Spiekstra, et al.. (2022). Proof-of-Concept Organ-on-Chip Study: Topical Cinnamaldehyde Exposure of Reconstructed Human Skin with Integrated Neopapillae Cultured under Dynamic Flow. Pharmaceutics. 14(8). 1529–1529. 17 indexed citations
6.
7.
Kühnl, Jochen, Ursula Müller‐Vieira, Camille Géniès, et al.. (2020). Characterization of application scenario-dependent pharmacokinetics and pharmacodynamic properties of permethrin and hyperforin in a dynamic skin and liver multi-organ-chip model. Toxicology. 448. 152637–152637. 42 indexed citations
8.
Mühleder, Severin, Krystyna Labuda, Eleni Priglinger, et al.. (2018). The role of fibrinolysis inhibition in engineered vascular networks derived from endothelial cells and adipose-derived stem cells. Stem Cell Research & Therapy. 9(1). 261–261. 27 indexed citations
9.
Mühleder, Severin, Katharina Schimek, Tobias Hasenberg, et al.. (2017). Engineering Blood and Lymphatic Microvascular Networks in Fibrin Matrices. Frontiers in Bioengineering and Biotechnology. 5. 25–25. 73 indexed citations
10.
Materne, Eva-Maria, Ilka Maschmeyer, Alexandra Lorenz, et al.. (2015). The Multi-organ Chip - A Microfluidic Platform for Long-term Multi-tissue Coculture. Journal of Visualized Experiments. 21 indexed citations
11.
Maschmeyer, Ilka, Tobias Hasenberg, Marcus Lindner, et al.. (2015). Chip-based human liver-intestine and liver-skin co-culture. DepositOnce. 1 indexed citations
12.
Schimek, Katharina, Mathias Busek, Silke Hoffmann, et al.. (2013). Integrating biological vasculature into a multi-organ-chip microsystem. Lab on a Chip. 13(18). 3588–3588. 145 indexed citations
13.
Marx, Uwe. (2012). Trends in Cell Culture Technology. Advances in experimental medicine and biology. 745. 26–46. 14 indexed citations
14.
Gernaey, Krist V., Frank Baganz, Ezequiel Franco‐Lara, et al.. (2012). Monitoring and control of microbioreactors: An expert opinion on development needs. Biotechnology Journal. 7(10). 1308–1314. 27 indexed citations
15.
Horland, Reyk, G Lindner, Ilka Wagner, et al.. (2011). Human hair follicle equivalents in vitro for transplantation and chip-based substance testing. BMC Proceedings. 5(S8). O7–O7. 3 indexed citations
16.
Blanchard, Véronique, Xi Liu, Matthias Kaup, et al.. (2011). N‐glycosylation and biological activity of recombinant human alpha1‐antitrypsin expressed in a novel human neuronal cell line. Biotechnology and Bioengineering. 108(9). 2118–2128. 49 indexed citations
17.
Sonntag, Frank, Udo Klotzbach, G Lindner, et al.. (2010). Design and prototyping of a chip-based multi-micro-organoid culture system for substance testing, predictive to human (substance) exposure. Journal of Biotechnology. 148(1). 70–75. 52 indexed citations
18.
Giese, Christoph, et al.. (2006). A Human Lymph Node In Vitro—Challenges and Progress. Artificial Organs. 30(10). 803–808. 76 indexed citations
19.
Marx, Uwe, G. Laßmann, Kandatege Wimalasena, Peter Müller, & Andreas Herrmann. (1997). Rapid kinetics of insertion and accessibility of spin-labeled phospholipid analogs in lipid membranes: a stopped-flow electron paramagnetic resonance approach. Biophysical Journal. 73(3). 1645–1654. 16 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.

Explore authors with similar magnitude of impact

Rankless by CCL
2026