Michael Jendrusch

440 total citations
12 papers, 131 citations indexed

About

Michael Jendrusch is a scholar working on Molecular Biology, Genetics and Artificial Intelligence. According to data from OpenAlex, Michael Jendrusch has authored 12 papers receiving a total of 131 indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Molecular Biology, 3 papers in Genetics and 2 papers in Artificial Intelligence. Recurrent topics in Michael Jendrusch's work include CRISPR and Genetic Engineering (3 papers), Protein Structure and Dynamics (2 papers) and AI in cancer detection (2 papers). Michael Jendrusch is often cited by papers focused on CRISPR and Genetic Engineering (3 papers), Protein Structure and Dynamics (2 papers) and AI in cancer detection (2 papers). Michael Jendrusch collaborates with scholars based in Germany, United Kingdom and United States. Michael Jendrusch's co-authors include Iordania Constantinou, Matthias Kloor, Jakob Nikolas Kather, Alexander T. Pearson, Tom Luedde, Titus J. Brinker, Roman D. Buelow, Josien C.A. Jenniskens, Kelly Offermans and Amelie Echle and has published in prestigious journals such as Nature, Nucleic Acids Research and Nature Communications.

In The Last Decade

Michael Jendrusch

8 papers receiving 128 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Michael Jendrusch Germany	5	41	37	29	28	19	12	131
C. Ramírez United Kingdom	5	37 0.9×	19 0.5×	39 1.3×	41 1.5×	7 0.4×	6	249
Xueyu Liu China	9	65 1.6×	66 1.8×	22 0.8×	49 1.8×	43 2.3×	48	254
Marija Pizurica United States	5	21 0.5×	66 1.8×	47 1.6×	57 2.0×	15 0.8×	6	202
Gan Gao China	6	79 1.9×	28 0.8×	44 1.5×	18 0.6×	8 0.4×	14	153
Priya Khandelwal India	5	26 0.6×	57 1.5×	59 2.0×	53 1.9×	5 0.3×	6	216
Xiaochen Qin United States	7	101 2.5×	14 0.4×	46 1.6×	5 0.2×	8 0.4×	13	167
Davood Khezerloo Iran	9	76 1.9×	74 2.0×	27 0.9×	173 6.2×	9 0.5×	24	295
Elizabeth Lee United States	7	56 1.4×	17 0.5×	44 1.5×	13 0.5×	15 0.8×	14	164
Joanna Filippi Italy	10	142 3.5×	20 0.5×	34 1.2×	16 0.6×	22 1.2×	30	250
Aman Rana United States	6	25 0.6×	75 2.0×	22 0.8×	34 1.2×	35 1.8×	16	185

Countries citing papers authored by Michael Jendrusch

Since Specialization

Citations

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

Fields of papers citing papers by Michael Jendrusch

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Michael Jendrusch

This figure shows the co-authorship network connecting the top 25 collaborators of Michael Jendrusch. A scholar is included among the top collaborators of Michael Jendrusch 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 Michael Jendrusch. Michael Jendrusch is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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12 of 12 papers shown

Andrades, Álvaro, Michael Jendrusch, Sonia Zumalave, et al.. (2025). Origins of chromosome instability unveiled by coupled imaging and genomics. Nature. 648(8093). 383–393.

Jendrusch, Michael, Elisabetta Cacace, Jacob Bobonis, et al.. (2025). AlphaDesign: a de novo protein design framework based on AlphaFold. Molecular Systems Biology. 21(9). 1166–1189. 3 indexed citations

Jendrusch, Michael & Jan O. Korbel. (2025). Efficient protein structure generation with sparse denoising models. Nature Machine Intelligence. 7(9). 1429–1445.

Aschenbrenner, Sabine, Felix Bubeck, Michael Jendrusch, et al.. (2025). A versatile anti-CRISPR platform for opto- and chemogenetic control of CRISPR-Cas9 and Cas12 across a wide range of orthologs.. PubMed. 53(14).

Heid, Daniel, Michael Jendrusch, Sabine Aschenbrenner, et al.. (2024). A deep mutational scanning platform to characterize the fitness landscape of anti-CRISPR proteins. Nucleic Acids Research. 52(22). e103–e103.

Höps, Wolfram, et al.. (2024). Impact and characterization of serial structural variations across humans and great apes. Nature Communications. 15(1). 8007–8007. 4 indexed citations

Niehues, Jan, Gustav Müller‐Franzes, Sophia J. Wagner, et al.. (2024). Using histopathology latent diffusion models as privacy-preserving dataset augmenters improves downstream classification performance. Computers in Biology and Medicine. 175. 108410–108410. 5 indexed citations

Haupt, Saskia, Aysel Ahadova, Alexej Ballhausen, et al.. (2022). A simple approach for detecting HLA‐A*02 alleles in archival formalin‐fixed paraffin‐embedded tissue samples and an application example for studying cancer immunoediting. HLA. 101(1). 24–33. 3 indexed citations

Krause, Jeremias, Heike I. Grabsch, Matthias Kloor, et al.. (2021). Deep learning detects genetic alterations in cancer histology generated by adversarial networks. The Journal of Pathology. 254(1). 70–79. 51 indexed citations

10.

Belzen, Julius Upmeier zu, Felix Bubeck, Moritz J. Przybilla, et al.. (2019). Leveraging implicit knowledge in neural networks for functional dissection and engineering of proteins. Nature Machine Intelligence. 1(5). 225–235. 19 indexed citations

11.

Jendrusch, Michael, et al.. (2019). Spatially resolved electrical impedance methods for cell and particle characterization. Electrophoresis. 41(1-2). 65–80. 30 indexed citations

12.

Constantinou, Iordania, et al.. (2019). Self-Learning Microfluidic Platform for Single-Cell Imaging and Classification in Flow. Micromachines. 10(5). 311–311. 16 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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