Katja Luck

5.1k total citations · 1 hit paper
25 papers, 1.1k citations indexed

About

Katja Luck is a scholar working on Molecular Biology, Cell Biology and Genetics. According to data from OpenAlex, Katja Luck has authored 25 papers receiving a total of 1.1k indexed citations (citations by other indexed papers that have themselves been cited), including 24 papers in Molecular Biology, 3 papers in Cell Biology and 3 papers in Genetics. Recurrent topics in Katja Luck's work include Protein Structure and Dynamics (8 papers), Bioinformatics and Genomic Networks (7 papers) and Microbial Metabolic Engineering and Bioproduction (4 papers). Katja Luck is often cited by papers focused on Protein Structure and Dynamics (8 papers), Bioinformatics and Genomic Networks (7 papers) and Microbial Metabolic Engineering and Bioproduction (4 papers). Katja Luck collaborates with scholars based in Germany, United States and France. Katja Luck's co-authors include Gilles Travé, Marc Vidal, Sébastian Charbonnier, Stephanie J. Ruiz, Bert Poolman, Ina L. Urbatsch, Frans Bianchi, Ivy Zhang, Gloria Sheynkman and Nishka Kishore and has published in prestigious journals such as Nucleic Acids Research, Nature Communications and The EMBO Journal.

In The Last Decade

Katja Luck

22 papers receiving 1.1k citations

Hit Papers

Network-based prediction of protein interactions 2019 2026 2021 2023 2019 50 100 150 200 250

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Katja Luck Germany 15 755 146 113 94 80 25 1.1k
Tau‐Mu Yi United States 18 1.5k 2.0× 149 1.0× 85 0.8× 88 0.9× 79 1.0× 40 1.8k
Yoon Sup Choi South Korea 9 632 0.8× 121 0.8× 38 0.3× 64 0.7× 29 0.4× 12 870
Lan V. Zhang United States 7 1.7k 2.2× 96 0.7× 285 2.5× 122 1.3× 36 0.5× 7 1.9k
Michael Livstone United States 9 2.2k 3.0× 175 1.2× 380 3.4× 83 0.9× 40 0.5× 10 2.8k
Andrew Mugler United States 19 836 1.1× 182 1.2× 46 0.4× 113 1.2× 32 0.4× 60 1.2k
Denis Dupuy France 16 2.2k 2.9× 217 1.5× 264 2.3× 157 1.7× 65 0.8× 29 2.8k
Pablo Mier Germany 15 735 1.0× 37 0.3× 40 0.4× 59 0.6× 74 0.9× 52 932
John Wagner Australia 19 831 1.1× 170 1.2× 24 0.2× 88 0.9× 97 1.2× 30 1.4k
Martin H. Schaefer Germany 24 1.5k 2.1× 134 0.9× 213 1.9× 16 0.2× 26 0.3× 43 2.0k
Ney Lemke Brazil 19 877 1.2× 30 0.2× 219 1.9× 64 0.7× 50 0.6× 62 1.3k

Countries citing papers authored by Katja Luck

Since Specialization
Citations

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

Fields of papers citing papers by Katja Luck

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Katja Luck

This figure shows the co-authorship network connecting the top 25 collaborators of Katja Luck. A scholar is included among the top collaborators of Katja Luck 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 Katja Luck. Katja Luck 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.
Luck, Katja, et al.. (2025). Bias in, bias out – AlphaFold-Multimer and the structural complexity of protein interfaces. Current Opinion in Structural Biology. 91. 103002–103002. 5 indexed citations
2.
Matias, Ana Catarina, Francesca Torelli, Tania Medeiros, et al.. (2025). Toxoplasma effector TgROP1 establishes membrane contact sites with the endoplasmic reticulum during infection. Nature Microbiology. 10(12). 3331–3345.
3.
Skinnider, Michael A., Katja Luck, M. Shahid Mukhtar, et al.. (2025). What is the current bottleneck in mapping molecular interaction networks?. Cell Systems. 16(5). 101295–101295.
4.
Casas-Delucchi, Corella S., Paulina Prorok, Sunil Kumar Pradhan, et al.. (2024). Histone variant macroH2A1 regulates synchronous firing of replication origins in the inactive X chromosome. Nucleic Acids Research. 52(19). 11659–11688.
6.
Varga, Julia K., Christian Schäfer, M Welzel, et al.. (2024). Systematic discovery of protein interaction interfaces using AlphaFold and experimental validation. Molecular Systems Biology. 20(2). 75–97. 41 indexed citations
7.
Bronkhorst, Alfred W., Martin M. Möckel, António Miguel de Jesus Domingues, et al.. (2023). An extended Tudor domain within Vreteno interconnects Gtsf1L and Ago3 for piRNA biogenesis in Bombyx mori. The EMBO Journal. 42(24). e114072–e114072. 7 indexed citations
8.
Luck, Katja, et al.. (2023). RNA-dependent interactome allows network-based assignment of RNA-binding protein function. Nucleic Acids Research. 51(10). 5162–5176. 4 indexed citations
9.
Freiwald, Anja, Ramona Schmitt, Mario Dejung, et al.. (2022). Proteome effects of genome-wide single gene perturbations. Nature Communications. 13(1). 6153–6153. 12 indexed citations
10.
Helmy, Mohamed, Miles W. Mee, Tong Hao, et al.. (2022). OpenPIP: An Open-source Platform for Hosting, Visualizing and Analyzing Protein Interaction Data. Journal of Molecular Biology. 434(11). 167603–167603. 5 indexed citations
11.
Yadav, Anupama, Marc Vidal, & Katja Luck. (2020). Precision medicine — networks to the rescue. Current Opinion in Biotechnology. 63. 177–189. 21 indexed citations
12.
Kovács, I., Katja Luck, Kerstin Spirohn, et al.. (2019). Network-based prediction of protein interactions. Nature Communications. 10(1). 1240–1240. 283 indexed citations breakdown →
13.
Martínez-Noël, Gustavo, Katja Luck, Simone Kühnle, et al.. (2018). Network Analysis of UBE3A/E6AP-Associated Proteins Provides Connections to Several Distinct Cellular Processes. Journal of Molecular Biology. 430(7). 1024–1050. 36 indexed citations
14.
Luck, Katja, Gloria Sheynkman, Ivy Zhang, & Marc Vidal. (2017). Proteome-Scale Human Interactomics. Trends in Biochemical Sciences. 42(5). 342–354. 91 indexed citations
15.
Bianchi, Frans, et al.. (2016). Asymmetry in inward- and outward-affinity constant of transport explain unidirectional lysine flux in Saccharomyces cerevisiae. Scientific Reports. 6(1). 31443–31443. 199 indexed citations
16.
Vincentelli, Renaud, Katja Luck, Juline Poirson, et al.. (2015). Quantifying domain-ligand affinities and specificities by high-throughput holdup assay. Nature Methods. 12(8). 787–793. 59 indexed citations
17.
Luck, Katja, Sébastian Charbonnier, & Gilles Travé. (2012). The emerging contribution of sequence context to the specificity of protein interactions mediated by PDZ domains. FEBS Letters. 586(17). 2648–2661. 95 indexed citations
18.
Charbonnier, Sébastian, Yves Nominé, Juan Antonio Ortega, et al.. (2011). The Structural and Dynamic Response of MAGI-1 PDZ1 with Noncanonical Domain Boundaries to the Binding of Human Papillomavirus E6. Journal of Molecular Biology. 406(5). 745–763. 44 indexed citations
19.
Luck, Katja, et al.. (2011). Putting into Practice Domain-Linear Motif Interaction Predictions for Exploration of Protein Networks. PLoS ONE. 6(11). e25376–e25376. 33 indexed citations
20.
Diella, Francesca, Sophie Chabanis, Katja Luck, et al.. (2008). KEPE—a motif frequently superimposed on sumoylation sites in metazoan chromatin proteins and transcription factors. Bioinformatics. 25(1). 1–5. 24 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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