Silke Hauf

4.7k total citations · 2 hit papers
36 papers, 3.7k citations indexed

About

Silke Hauf is a scholar working on Molecular Biology, Cell Biology and Plant Science. According to data from OpenAlex, Silke Hauf has authored 36 papers receiving a total of 3.7k indexed citations (citations by other indexed papers that have themselves been cited), including 29 papers in Molecular Biology, 27 papers in Cell Biology and 11 papers in Plant Science. Recurrent topics in Silke Hauf's work include Microtubule and mitosis dynamics (25 papers), Genomics and Chromatin Dynamics (15 papers) and Chromosomal and Genetic Variations (5 papers). Silke Hauf is often cited by papers focused on Microtubule and mitosis dynamics (25 papers), Genomics and Chromatin Dynamics (15 papers) and Chromosomal and Genetic Variations (5 papers). Silke Hauf collaborates with scholars based in Germany, United States and Austria. Silke Hauf's co-authors include Jan‐Michael Peters, Irene C. Waizenegger, Andreas Meinke, Jan‐Michael Peters, Yoshinori Watanabe, Gisela Schnapp, Richard W. Cole, Armin Heckel, Jacques Van Meel and Christine L. Zimmer and has published in prestigious journals such as Science, Cell and Nucleic Acids Research.

In The Last Decade

Silke Hauf

35 papers receiving 3.7k citations

Hit Papers

The small molecule Hesperadin reveals a role for Aurora B... 2000 2026 2008 2017 2003 2000 250 500 750

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Silke Hauf Germany 22 3.3k 2.6k 972 487 170 36 3.7k
Irene C. Waizenegger Austria 20 2.8k 0.8× 1.7k 0.7× 924 1.0× 417 0.9× 176 1.0× 31 3.4k
Marta Gálová Austria 13 3.9k 1.2× 2.4k 0.9× 1.0k 1.0× 347 0.7× 187 1.1× 15 4.2k
Wolfgang Zachariae Germany 25 4.5k 1.4× 2.9k 1.1× 850 0.9× 529 1.1× 224 1.3× 33 5.0k
Oliver J. Gruß Germany 29 3.1k 0.9× 2.1k 0.8× 372 0.4× 301 0.6× 240 1.4× 48 3.6k
Jesse Lipp Austria 14 2.5k 0.8× 1.2k 0.4× 429 0.4× 419 0.9× 144 0.8× 20 2.8k
Régis Giet France 20 2.2k 0.7× 2.1k 0.8× 494 0.5× 762 1.6× 149 0.9× 40 2.8k
Gerben Vader Netherlands 17 1.9k 0.6× 1.4k 0.5× 389 0.4× 529 1.1× 118 0.7× 26 2.2k
Damien F. Hudson Australia 24 2.3k 0.7× 938 0.4× 749 0.8× 299 0.6× 235 1.4× 38 2.6k
Jill M. Schumacher United States 21 2.8k 0.8× 1.6k 0.6× 421 0.4× 1.2k 2.5× 211 1.2× 30 3.5k
Didier Fesquet France 27 2.5k 0.8× 1.6k 0.6× 313 0.3× 958 2.0× 207 1.2× 36 3.0k

Countries citing papers authored by Silke Hauf

Since Specialization
Citations

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

Fields of papers citing papers by Silke Hauf

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Silke Hauf

This figure shows the co-authorship network connecting the top 25 collaborators of Silke Hauf. A scholar is included among the top collaborators of Silke Hauf 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 Silke Hauf. Silke Hauf 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.
Brenna, Greta, et al.. (2026). Love-thy-neighbor: neural networks for tracking and lineage tracing in budding yeast. Bioinformatics Advances. 6(1).
2.
Singh, Abhyudai, et al.. (2023). The minimal intrinsic stochasticity of constitutively expressed eukaryotic genes is sub-Poissonian. Science Advances. 9(32). eadh5138–eadh5138. 23 indexed citations
3.
Hauf, Silke, et al.. (2023). Sock and Environmental Swabs as an Efficient, Non-Invasive Tool to Assess the Salmonella Status of Sow Farms. Animals. 13(6). 1031–1031. 2 indexed citations
4.
Chen, Jing, et al.. (2022). Mitotic checkpoint gene expression is tuned by codon usage bias. The EMBO Journal. 41(15). e107896–e107896. 7 indexed citations
5.
Xu, Zhengyao, et al.. (2021). Mutation and selection explain why many eukaryotic centromeric DNA sequences are often A + T rich. Nucleic Acids Research. 50(1). 579–596. 7 indexed citations
6.
Hauf, Silke, et al.. (2020). Pomegranate: 2D segmentation and 3D reconstruction for fission yeast and other radially symmetric cells. Scientific Reports. 10(1). 16580–16580. 5 indexed citations
7.
Groß, Fridolin, et al.. (2018). Implications of alternative routes to APC/C inhibition by the mitotic checkpoint complex. PLoS Computational Biology. 14(9). e1006449–e1006449. 10 indexed citations
8.
Hauf, Silke, et al.. (2017). Different Functionality of Cdc20 Binding Sites within the Mitotic Checkpoint Complex. Current Biology. 27(8). 1213–1220. 21 indexed citations
9.
Koch, André, et al.. (2017). Construction, Growth, and Harvesting of Fission Yeast Stable Isotope Labeling by Amino Acids in Cell Culture (SILAC) Strains. Cold Spring Harbor Protocols. 2017(6). pdb.prot091678–pdb.prot091678. 4 indexed citations
10.
Kamenz, Julia & Silke Hauf. (2014). Slow Checkpoint Activation Kinetics as a Safety Device in Anaphase. Current Biology. 24(6). 646–651. 14 indexed citations
11.
Heinrich, Stephanie, Hanna Windecker, Maria Langegger, et al.. (2014). Mad1 contribution to spindle assembly checkpoint signalling goes beyond presenting M ad2 at kinetochores. EMBO Reports. 15(3). 291–298. 45 indexed citations
12.
Heinrich, Stephanie, Julia Kamenz, Susanne Trautmann, et al.. (2013). Determinants of robustness in spindle assembly checkpoint signalling. Nature Cell Biology. 15(11). 1328–1339. 83 indexed citations
13.
Heinrich, Stephanie, Hanna Windecker, Nicole Hustedt, & Silke Hauf. (2012). Mph1 kinetochore localization is crucial and upstream in the hierarchy of spindle assembly checkpoint protein recruitment to kinetochores. Journal of Cell Science. 125(Pt 20). 4720–7. 46 indexed citations
14.
Sakuno, Takeshi, Kōichi Tanaka, Silke Hauf, & Yoshinori Watanabe. (2011). Repositioning of Aurora B Promoted by Chiasmata Ensures Sister Chromatid Mono-Orientation in Meiosis I. Developmental Cell. 21(3). 534–545. 54 indexed citations
15.
Koch, André & Silke Hauf. (2010). Strategies for the identification of kinase substrates using analog-sensitive kinases. European Journal of Cell Biology. 89(2-3). 184–193. 24 indexed citations
16.
Kawashima, Shigehiro A., Tatsuya Tsukahara, Maria Langegger, et al.. (2007). Shugoshin enables tension-generating attachment of kinetochores by loading Aurora to centromeres. Genes & Development. 21(4). 420–435. 164 indexed citations
17.
Hauf, Silke, et al.. (2007). Aurora controls sister kinetochore mono-orientation and homolog bi-orientation in meiosis-I. The EMBO Journal. 26(21). 4475–4486. 73 indexed citations
18.
Kitajima, Tomoya S., Silke Hauf, Miho Ohsugi, Tadashi Yamamoto, & Yoshinori Watanabe. (2005). Human Bub1 Defines the Persistent Cohesion Site along the Mitotic Chromosome by Affecting Shugoshin Localization. Current Biology. 15(4). 353–359. 206 indexed citations
19.
Hauf, Silke & Yoshinori Watanabe. (2004). Kinetochore Orientation in Mitosis and Meiosis. Cell. 119(3). 317–327. 96 indexed citations
20.
Waizenegger, Irene C., Silke Hauf, Andreas Meinke, & Jan‐Michael Peters. (2000). Two Distinct Pathways Remove Mammalian Cohesin from Chromosome Arms in Prophase and from Centromeres in Anaphase. Cell. 103(3). 399–410. 577 indexed citations breakdown →

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