Tim Clausen

10.4k total citations · 2 hit papers
102 papers, 7.1k citations indexed

About

Tim Clausen is a scholar working on Molecular Biology, Materials Chemistry and Genetics. According to data from OpenAlex, Tim Clausen has authored 102 papers receiving a total of 7.1k indexed citations (citations by other indexed papers that have themselves been cited), including 70 papers in Molecular Biology, 48 papers in Materials Chemistry and 21 papers in Genetics. Recurrent topics in Tim Clausen's work include Enzyme Structure and Function (48 papers), Bacterial Genetics and Biotechnology (21 papers) and Protein Structure and Dynamics (18 papers). Tim Clausen is often cited by papers focused on Enzyme Structure and Function (48 papers), Bacterial Genetics and Biotechnology (21 papers) and Protein Structure and Dynamics (18 papers). Tim Clausen collaborates with scholars based in Austria, Germany and United Kingdom. Tim Clausen's co-authors include Michael Ehrmann, Robert Huber, T. Krojer, Christopher Southan, Markus Kaiser, Justyna Sawa‐Makarska, R Kurzbauer, Albrecht Messerschmidt, Karl Mechtler and Bernd Laber and has published in prestigious journals such as Nature, Science and Cell.

In The Last Decade

Tim Clausen

100 papers receiving 7.0k citations

Hit Papers

The HtrA Family of Proteases 2002 2026 2010 2018 2002 2022 100 200 300 400 500

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Tim Clausen Austria 47 4.7k 1.3k 1.2k 753 700 102 7.1k
Robert Schwarzenbacher United States 33 4.8k 1.0× 310 0.2× 579 0.5× 408 0.5× 641 0.9× 51 6.7k
Dirk Jan Slotboom Netherlands 43 3.4k 0.7× 477 0.4× 1.0k 0.9× 91 0.1× 330 0.5× 117 5.1k
Markus Kaiser Germany 49 4.0k 0.9× 306 0.2× 288 0.2× 243 0.3× 535 0.8× 204 6.6k
Didier Vertommen Belgium 52 5.4k 1.2× 394 0.3× 769 0.7× 82 0.1× 708 1.0× 193 7.8k
Nam‐Chul Ha South Korea 42 4.0k 0.8× 527 0.4× 863 0.7× 118 0.2× 360 0.5× 219 6.8k
Oriano Marin Italy 43 4.4k 0.9× 334 0.3× 524 0.4× 156 0.2× 863 1.2× 165 6.0k
M J Runswick United Kingdom 16 5.9k 1.2× 533 0.4× 1.2k 1.0× 118 0.2× 588 0.8× 17 7.9k
Tony Atkinson United Kingdom 39 3.0k 0.6× 1.3k 1.0× 486 0.4× 304 0.4× 309 0.4× 149 4.3k
Gourisankar Ghosh United States 55 7.2k 1.5× 361 0.3× 574 0.5× 100 0.1× 672 1.0× 138 11.3k
Åke Engström Sweden 47 4.8k 1.0× 456 0.3× 729 0.6× 59 0.1× 442 0.6× 112 8.7k

Countries citing papers authored by Tim Clausen

Since Specialization
Citations

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

Fields of papers citing papers by Tim Clausen

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Tim Clausen

This figure shows the co-authorship network connecting the top 25 collaborators of Tim Clausen. A scholar is included among the top collaborators of Tim Clausen 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 Tim Clausen. Tim Clausen 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.
Yagita, Yuichi, Paul V. Murphy, R Kurzbauer, et al.. (2025). Convergence of orphan quality control pathways at a ubiquitin chain-elongating ligase. Molecular Cell. 85(4). 815–828.e10. 5 indexed citations
2.
Grabarczyk, Daniel B., Paul V. Murphy, R Kurzbauer, et al.. (2025). Architecture of the UBR4 complex, a giant E4 ligase central to eukaryotic protein quality control. Science. 389(6763). 909–914. 2 indexed citations
3.
Deszcz, Luiza, et al.. (2024). UNC-45 assisted myosin folding depends on a conserved FX3HY motif implicated in Freeman Sheldon Syndrome. Nature Communications. 15(1). 6272–6272. 2 indexed citations
4.
Picchianti, Lorenzo, Víctor Sánchez de Medina Hernández, Ni Zhan, et al.. (2023). Shuffled ATG8 interacting motifs form an ancestral bridge between UFMylation and autophagy. The EMBO Journal. 42(10). e112053–e112053. 29 indexed citations
5.
Schäfer, Markus, et al.. (2023). HUWE1 controls tristetraprolin proteasomal degradation by regulating its phosphorylation. eLife. 12. 6 indexed citations
6.
Grishkovskaya, Irina, Adar Sonn-Segev, Manish S. Kushwah, et al.. (2021). The linear ubiquitin chain assembly complex (LUBAC) generates heterotypic ubiquitin chains. eLife. 10. 38 indexed citations
7.
Suskiewicz, Marcin J., Nikolas Hundt, Anton Meinhart, et al.. (2021). McsB forms a gated kinase chamber to mark aberrant bacterial proteins for degradation. eLife. 10. 16 indexed citations
8.
Loll, Bernhard, et al.. (2014). RNA Specificity and Regulation of Catalysis in the Eukaryotic Polynucleotide Kinase Clp1. Molecular Cell. 54(6). 975–986. 18 indexed citations
9.
Trentini, Débora Broch, Jakob Fuhrmann, Karl Mechtler, & Tim Clausen. (2014). Chasing Phosphoarginine Proteins: Development of a Selective Enrichment Method Using a Phosphatase Trap. Molecular & Cellular Proteomics. 13(8). 1953–1964. 47 indexed citations
10.
Schmidt, Andreas, Débora Broch Trentini, Jakob Fuhrmann, et al.. (2013). Quantitative Phosphoproteomics Reveals the Role of Protein Arginine Phosphorylation in the Bacterial Stress Response. Molecular & Cellular Proteomics. 13(2). 537–550. 94 indexed citations
11.
Hellerschmied, Doris & Tim Clausen. (2013). Myosin chaperones. Current Opinion in Structural Biology. 25. 9–15. 26 indexed citations
12.
Tennstaedt, Annette, Linda Truebestein, Patrick Hauske, et al.. (2012). Human High Temperature Requirement Serine Protease A1 (HTRA1) Degrades Tau Protein Aggregates. Journal of Biological Chemistry. 287(25). 20931–20941. 73 indexed citations
13.
Hauske, Patrick, Sonja Hasenbein, Christian Ottmann, et al.. (2009). Peptidic small molecule activators of the stress sensor DegS. Molecular BioSystems. 5(9). 980–985. 12 indexed citations
15.
Worbs, Michael, Clemens Steegborn, M.C. Wahl, et al.. (2003). Determinants of Enzymatic Specificity in the Cys-Met-Metabolism PLP-Dependent Enzyme Family: Crystal Structure of Cystathionine γ-Lyase from Yeast and Intrafamiliar Structure Comparison. Biological Chemistry. 384(3). 373–86. 92 indexed citations
16.
Clausen, Tim, Christopher Southan, & Michael Ehrmann. (2002). The HtrA Family of Proteases. Molecular Cell. 10(3). 443–455. 523 indexed citations breakdown →
17.
Laber, Bernd, et al.. (2001). Structural Basis for the Function of Pyridoxine 5′-Phosphate Synthase. Structure. 9(3). 245–253. 22 indexed citations
18.
Steegborn, Clemens, Bernd Laber, Albrecht Messerschmidt, Robert Huber, & Tim Clausen. (2001). Crystal structures of cystathionine γ-synthase inhibitor complexes rationalize the increased affinity of a novel inhibitor. Journal of Molecular Biology. 311(4). 789–801. 21 indexed citations
19.
Wahl, M.C., Robert Huber, Lars Prade, et al.. (1997). Cloning, purification, crystallization, and preliminary X‐ray diffraction analysis of cystathionine γ‐synthase from E. coli. FEBS Letters. 414(3). 492–496. 13 indexed citations
20.
Laber, Bernd, Tim Clausen, Robert Huber, et al.. (1996). Cloning, purification, and crystallization of Escherichia coli cystathionine β‐lyase. FEBS Letters. 379(1). 94–96. 12 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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