Daniel Kümmel

2.9k total citations
67 papers, 1.8k citations indexed

About

Daniel Kümmel is a scholar working on Molecular Biology, Cell Biology and Physiology. According to data from OpenAlex, Daniel Kümmel has authored 67 papers receiving a total of 1.8k indexed citations (citations by other indexed papers that have themselves been cited), including 49 papers in Molecular Biology, 38 papers in Cell Biology and 12 papers in Physiology. Recurrent topics in Daniel Kümmel's work include Cellular transport and secretion (35 papers), Calcium signaling and nucleotide metabolism (12 papers) and Lipid Membrane Structure and Behavior (12 papers). Daniel Kümmel is often cited by papers focused on Cellular transport and secretion (35 papers), Calcium signaling and nucleotide metabolism (12 papers) and Lipid Membrane Structure and Behavior (12 papers). Daniel Kümmel collaborates with scholars based in Germany, United States and Netherlands. Daniel Kümmel's co-authors include Christian Ungermann, Udo Heinemann, Karin M. Reinisch, Lars Langemeyer, Feng Li, Konrad Büssow, Frédéric Pincet, James E. Rothman, Christoph Scheich and Shyam S. Krishnakumar and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Journal of the American Chemical Society and Nucleic Acids Research.

In The Last Decade

Daniel Kümmel

62 papers receiving 1.8k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Daniel Kümmel Germany 25 1.3k 1.1k 259 242 210 67 1.8k
Aymelt Itzen Germany 29 1.8k 1.4× 1.2k 1.1× 199 0.8× 267 1.1× 329 1.6× 75 2.9k
Alex H. Hutagalung United States 12 1.4k 1.1× 1.1k 1.0× 156 0.6× 197 0.8× 177 0.8× 13 2.0k
Adriana L. Rojas Spain 19 940 0.7× 644 0.6× 135 0.5× 266 1.1× 169 0.8× 44 1.6k
Angelika Giner Germany 12 1.4k 1.1× 988 0.9× 155 0.6× 245 1.0× 106 0.5× 14 1.9k
Dániel Ungár United Kingdom 24 1.5k 1.2× 1.3k 1.2× 210 0.8× 359 1.5× 84 0.4× 40 2.0k
Jack Rohrer Switzerland 26 1.6k 1.3× 1.2k 1.1× 168 0.6× 386 1.6× 197 0.9× 45 2.4k
Sandro Vivona United States 14 816 0.6× 511 0.5× 142 0.5× 198 0.8× 434 2.1× 24 1.5k
Xudong Wu United States 16 1.1k 0.9× 813 0.8× 85 0.3× 139 0.6× 172 0.8× 25 1.6k
Marijn G. J. Ford United States 12 2.1k 1.7× 1.9k 1.7× 112 0.4× 375 1.5× 109 0.5× 21 2.7k
Jennifer Lippincott‐Schwartz United States 8 1.3k 1.0× 1.1k 1.0× 129 0.5× 183 0.8× 139 0.7× 9 2.0k

Countries citing papers authored by Daniel Kümmel

Since Specialization
Citations

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

Fields of papers citing papers by Daniel Kümmel

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Daniel Kümmel

This figure shows the co-authorship network connecting the top 25 collaborators of Daniel Kümmel. A scholar is included among the top collaborators of Daniel Kümmel 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 Daniel Kümmel. Daniel Kümmel 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.
Dörner, Wolfgang, et al.. (2025). Structural Basis for a Scaffolding Role of the COM Domain in Nonribosomal Peptide Synthetases. Angewandte Chemie International Edition. 64(36). e202506621–e202506621.
3.
Collado, Javier, Jenny Keller, Mike Wälte, et al.. (2025). The Myo2 adaptor Ldm1 and its receptor Ldo16 mediate actin-dependent lipid droplet motility. Cell Reports. 44(11). 116475–116475.
4.
Verma, Archana, Harald Nüsse, Jürgen Klingauf, et al.. (2025). RalGAP complexes control secretion and primary cilia in pancreatic disease. Life Science Alliance. 8(8). e202403123–e202403123. 1 indexed citations
5.
Mitton-Fry, Rachel M., et al.. (2024). Chemo-enzymatic production of base-modified ATP analogues for polyadenylation of RNA. Chemical Science. 15(32). 13068–13073. 8 indexed citations
6.
König, Simone, et al.. (2024). Unraveling key steps in the biosynthesis of antimicrobial methylated unsaturated 2-alkyl-4-quinolones of Burkholderia thailandensis. Cell Reports Physical Science. 5(8). 102100–102100. 2 indexed citations
7.
Moeller, Arne, et al.. (2023). Regulatory sites in the Mon1–Ccz1 complex control Rab5 to Rab7 transition and endosome maturation. Proceedings of the National Academy of Sciences. 120(30). e2303750120–e2303750120. 14 indexed citations
8.
Eisenstein, Miriam, et al.. (2023). Structural and biochemical analysis of a novel atypically split intein reveals a conserved histidine specific to cysteine-less inteins. Chemical Science. 14(19). 5204–5213. 4 indexed citations
9.
Wollenhaupt, J., et al.. (2023). Novel starting points for fragment-based drug design against mycobacterial thioredoxin reductase identified using crystallographic fragment screening. Acta Crystallographica Section D Structural Biology. 79(9). 857–865. 2 indexed citations
10.
Klink, B.U., Claudia Antoni, Lars Langemeyer, et al.. (2022). Structure of the Mon1-Ccz1 complex reveals molecular basis of membrane binding for Rab7 activation. Proceedings of the National Academy of Sciences. 119(6). 19 indexed citations
11.
Brandt, Nico, Christian Haug, Daniel Kümmel, et al.. (2022). Generating FAIR research data in experimental tribology. Scientific Data. 9(1). 16 indexed citations
12.
Perz, Angela, Stephan Kiontke, Lars Langemeyer, et al.. (2022). Structure of the HOPS tethering complex, a lysosomal membrane fusion machinery. eLife. 11. 47 indexed citations
13.
Brohée, Laura, Claudia Antoni, Stephan Kiontke, et al.. (2021). TSC1 binding to lysosomal PIPs is required for TSC complex translocation and mTORC1 regulation. Molecular Cell. 81(13). 2705–2721.e8. 39 indexed citations
14.
Lynagh, Timothy, Stephan Kiontke, Anders Christiansen, et al.. (2020). Peptide Inhibitors of the α-Cobratoxin–Nicotinic Acetylcholine Receptor Interaction. Journal of Medicinal Chemistry. 63(22). 13709–13718. 18 indexed citations
15.
Ungermann, Christian & Daniel Kümmel. (2019). Structure of membrane tethers and their role in fusion. Traffic. 20(7). 479–490. 51 indexed citations
16.
Kümmel, Daniel, et al.. (2018). Multisubunit tethers in membrane fusion. Current Biology. 28(8). R417–R420. 22 indexed citations
17.
Langemeyer, Lars, Angela Perz, Daniel Kümmel, & Christian Ungermann. (2017). A guanine nucleotide exchange factor (GEF) limits Rab GTPase–driven membrane fusion. Journal of Biological Chemistry. 293(2). 731–739. 31 indexed citations
18.
Kuhlee, Anne, et al.. (2015). The Habc Domain of the SNARE Vam3 Interacts with the HOPS Tethering Complex to Facilitate Vacuole Fusion. Journal of Biological Chemistry. 290(9). 5405–5413. 30 indexed citations
19.
Kümmel, Daniel, et al.. (2010). Characterization of the self-palmitoylation activity of the transport protein particle component Bet3. Cellular and Molecular Life Sciences. 67(15). 2653–2664. 8 indexed citations
20.
Turnbull, A.P., Daniel Kümmel, Bianka Prinz, et al.. (2005). Structure of palmitoylated BET3: insights into TRAPP complex assembly and membrane localization. The EMBO Journal. 24(5). 875–884. 49 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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