Jan Lipfert

7.1k total citations
115 papers, 5.0k citations indexed

About

Jan Lipfert is a scholar working on Molecular Biology, Atomic and Molecular Physics, and Optics and Biomedical Engineering. According to data from OpenAlex, Jan Lipfert has authored 115 papers receiving a total of 5.0k indexed citations (citations by other indexed papers that have themselves been cited), including 86 papers in Molecular Biology, 38 papers in Atomic and Molecular Physics, and Optics and 24 papers in Biomedical Engineering. Recurrent topics in Jan Lipfert's work include DNA and Nucleic Acid Chemistry (40 papers), Force Microscopy Techniques and Applications (25 papers) and RNA and protein synthesis mechanisms (25 papers). Jan Lipfert is often cited by papers focused on DNA and Nucleic Acid Chemistry (40 papers), Force Microscopy Techniques and Applications (25 papers) and RNA and protein synthesis mechanisms (25 papers). Jan Lipfert collaborates with scholars based in Germany, Netherlands and United States. Jan Lipfert's co-authors include Sebastian Doniach, Nynke H. Dekker, Daniel Herschlag, Vincent B. Chu, Rhiju Das, Jacob Kerssemakers, Yu Bai, Linda Columbus, Tessa Jager and David Dulin and has published in prestigious journals such as Chemical Reviews, Proceedings of the National Academy of Sciences and Journal of the American Chemical Society.

In The Last Decade

Jan Lipfert

113 papers receiving 5.0k 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 Lipfert 3.6k 1.1k 1.0k 574 498 115 5.0k
Cristian Micheletti 3.6k 1.0× 749 0.7× 1.2k 1.2× 1.6k 2.7× 450 0.9× 168 5.3k
Jean‐François Allemand 3.6k 1.0× 1.5k 1.4× 1.8k 1.7× 656 1.1× 803 1.6× 88 5.8k
Matthew A. Young 4.2k 1.1× 1.4k 1.2× 481 0.5× 1.1k 1.9× 325 0.7× 53 6.7k
Daniel Harries 2.8k 0.8× 708 0.6× 812 0.8× 834 1.5× 206 0.4× 122 4.4k
Lois Pollack 3.1k 0.9× 951 0.9× 502 0.5× 992 1.7× 323 0.6× 117 4.6k
Robert M. Clegg 5.0k 1.4× 897 0.8× 604 0.6× 739 1.3× 257 0.5× 108 7.0k
Mathias Lösche 3.1k 0.9× 1.1k 1.0× 1.7k 1.6× 1.0k 1.8× 210 0.4× 105 5.8k
Don C. Lamb 4.1k 1.1× 882 0.8× 567 0.5× 1.1k 1.9× 299 0.6× 153 6.6k
Lars V. Schäfer 3.8k 1.1× 572 0.5× 1.1k 1.1× 1.1k 1.8× 165 0.3× 106 5.8k
D C Rau 2.4k 0.7× 833 0.7× 722 0.7× 406 0.7× 358 0.7× 31 4.0k

Countries citing papers authored by Jan Lipfert

Since Specialization
Citations

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

Fields of papers citing papers by Jan Lipfert

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jan Lipfert

This figure shows the co-authorship network connecting the top 25 collaborators of Jan Lipfert. A scholar is included among the top collaborators of Jan Lipfert 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 Lipfert. Jan Lipfert 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.
Chen, Li‐Ting, Myrthe Jager, Tom van den Ende, et al.. (2025). Nanopore-based consensus sequencing enables accurate multimodal tumor cell-free DNA profiling. Genome Research. 35(4). 886–899. 3 indexed citations
2.
Jiménez‐Rojo, Noemi, Suihan Feng, Johannes Morstein, et al.. (2025). Optical Control of Membrane Viscosity Modulates ER-to-Golgi Trafficking. ACS Central Science. 11(9). 1736–1752. 1 indexed citations
3.
Gebhardt, Christian, et al.. (2025). Labelizer: systematic selection of protein residues for covalent fluorophore labeling. Nature Communications. 16(1). 4147–4147. 1 indexed citations
4.
Pritzl, Stefanie D., et al.. (2025). Photoswitchable phospholipids for the optical control of membrane processes, protein function, and drug delivery. Communications Materials. 6(1). 59–59. 3 indexed citations
5.
Lak, Aidin, Yihao Wang, Marco Cassani, et al.. (2024). Cooperative dynamics of DNA-grafted magnetic nanoparticles optimize magnetic biosensing and coupling to DNA origami. Nanoscale. 16(15). 7678–7689. 4 indexed citations
6.
Pritzl, Stefanie D., et al.. (2024). Accurate drift-invariant single-molecule force calibration using the Hadamard variance. Biophysical Journal. 123(22). 3964–3976. 1 indexed citations
7.
Lipfert, Jan, et al.. (2024). Temperature-Dependent Twist of Double-Stranded RNA Probed by Magnetic Tweezer Experiments and Molecular Dynamics Simulations. The Journal of Physical Chemistry B. 128(3). 664–675. 6 indexed citations
8.
9.
Mathé, Jérôme, Sha Li, Pascal Martin, et al.. (2023). Thermally Switchable Nanogate Based on Polymer Phase Transition. Nano Letters. 23(11). 4862–4869. 7 indexed citations
10.
Dass, Mihir, Irina V. Martynenko, Relinde J. A. van Dijk‐Moes, et al.. (2023). DNA Origami Fiducial for Accurate 3D Atomic Force Microscopy Imaging. Nano Letters. 23(4). 1236–1243. 8 indexed citations
11.
Vanderlinden, Willem, et al.. (2023). Supercoiling-dependent DNA binding: quantitative modeling and applications to bulk and single-molecule experiments. Nucleic Acids Research. 52(1). 59–72. 6 indexed citations
12.
Cruz-León, Sergio, Willem Vanderlinden, Peter Müller, et al.. (2022). Twisting DNA by salt. Nucleic Acids Research. 50(10). 5726–5738. 42 indexed citations
13.
Vanderlinden, Willem, et al.. (2022). DNA fluctuations reveal the size and dynamics of topological domains. PNAS Nexus. 1(5). pgac268–pgac268. 9 indexed citations
14.
Bauer, Magnus S., Lukas F. Milles, Thomas Nicolaus, et al.. (2022). A tethered ligand assay to probe SARS-CoV-2:ACE2 interactions. Proceedings of the National Academy of Sciences. 119(14). e2114397119–e2114397119. 39 indexed citations
15.
Löf, Achim, Steffen M. Sedlak, Tobias Obser, et al.. (2019). Multiplexed protein force spectroscopy reveals equilibrium protein folding dynamics and the low-force response of von Willebrand factor. Proceedings of the National Academy of Sciences. 116(38). 18798–18807. 65 indexed citations
16.
Lipfert, Jan. (2018). Parallelized Magnetic Torque Tweezers Probe DNA Mechanics and Viral Integration. Biophysical Journal. 114(3). 596a–596a. 1 indexed citations
17.
Lipfert, Jan, et al.. (2014). Magnetic Tweezers for the Measurement of Twist and Torque. Journal of Visualized Experiments. 5 indexed citations
18.
Velthuis, Aartjan J.W. te, Jacob Kerssemakers, Jan Lipfert, & Nynke H. Dekker. (2011). Quantitative Guidelines for Force Calibration Through Spectral Analysis of Magnetic Tweezers Data. Biophysical Journal. 100(3). 481a–481a. 1 indexed citations
19.
Chu, Vincent B., Jan Lipfert, Yu Bai, et al.. (2009). Do conformational biases of simple helical junctions influence RNA folding stability and specificity?. RNA. 15(12). 2195–2205. 50 indexed citations
20.
Columbus, Linda, Jan Lipfert, Daniel A. Fox, et al.. (2009). Mixing and Matching Detergents for Membrane Protein NMR Structure Determination. Biophysical Journal. 96(3). 195a–195a. 2 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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