Michael M. Kaminski

2.2k total citations · 2 hit papers
22 papers, 1.5k citations indexed

About

Michael M. Kaminski is a scholar working on Molecular Biology, Epidemiology and Public Health, Environmental and Occupational Health. According to data from OpenAlex, Michael M. Kaminski has authored 22 papers receiving a total of 1.5k indexed citations (citations by other indexed papers that have themselves been cited), including 17 papers in Molecular Biology, 5 papers in Epidemiology and 4 papers in Public Health, Environmental and Occupational Health. Recurrent topics in Michael M. Kaminski's work include Renal and related cancers (9 papers), CRISPR and Genetic Engineering (6 papers) and Pluripotent Stem Cells Research (5 papers). Michael M. Kaminski is often cited by papers focused on Renal and related cancers (9 papers), CRISPR and Genetic Engineering (6 papers) and Pluripotent Stem Cells Research (5 papers). Michael M. Kaminski collaborates with scholars based in Germany, United States and Switzerland. Michael M. Kaminski's co-authors include James J. Collins, Feng Zhang, Omar O. Abudayyeh, Jonathan S. Gootenberg, Soeren S. Lienkamp, Sebastian J. Arnold, Peter Staeheli, Anand S. Dighe, Marta Broto and Hyemin Kim and has published in prestigious journals such as Nature Nanotechnology, Nature Cell Biology and Biomaterials.

In The Last Decade

Michael M. Kaminski

20 papers receiving 1.5k citations

Hit Papers

CRISPR-based diagnostics 2021 2026 2022 2024 2021 2022 250 500 750

Peers

Michael M. Kaminski
Koen Breyne United States
Tom Ferrante United States
Barrett R. Harvey United States
Vincent Idone United States
Michael M. Kaminski
Citations per year, relative to Michael M. Kaminski Michael M. Kaminski (= 1×) peers В. Н. Лазарев

Countries citing papers authored by Michael M. Kaminski

Since Specialization
Citations

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

Fields of papers citing papers by Michael M. Kaminski

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Michael M. Kaminski

This figure shows the co-authorship network connecting the top 25 collaborators of Michael M. Kaminski. A scholar is included among the top collaborators of Michael M. Kaminski 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 M. Kaminski. Michael M. Kaminski 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.
Yılmaz, Duygu Elif, Ria Schönauer, Kai‐Uwe Eckardt, et al.. (2025). In vivo base editing reduces liver cysts in autosomal dominant polycystic kidney disease. Molecular Therapy. 33(11). 5373–5382.
2.
Aird, Eric J., Grégoire Cullot, Maik Stein, et al.. (2025). Single-stranded HDR templates with truncated Cas12a-binding sequences improve knock-in efficiencies in primary human T cells. Molecular Therapy — Nucleic Acids. 36(2). 102568–102568. 1 indexed citations
3.
Lape, Isadora T., Jakob J. Metzger, Anand S. Dighe, et al.. (2024). CRISPR-enabled point-of-care genotyping for APOL1 genetic risk assessment. EMBO Molecular Medicine. 16(10). 2619–2637. 5 indexed citations
4.
Shakiba, Nika, Ross D. Jones, Michael M. Kaminski, et al.. (2023). Synthetic genetic circuits to uncover the OCT4 trajectories of successful reprogramming of human fibroblasts. Science Advances. 9(48). eadg8495–eadg8495. 10 indexed citations
5.
Kaminski, Michael M., et al.. (2022). HNF1B Alters an Evolutionarily Conserved Nephrogenic Program of Target Genes. Journal of the American Society of Nephrology. 34(3). 412–432. 10 indexed citations
6.
Tröndle, Kevin, Silvia Farè, Amandine Viau, et al.. (2022). Tuning the 3D microenvironment of reprogrammed tubule cells enhances biomimetic modeling of polycystic kidney disease. Biomaterials. 291. 121910–121910. 10 indexed citations
7.
Broto, Marta, Michael M. Kaminski, Nayoung Kim, et al.. (2022). Nanozyme-catalysed CRISPR assay for preamplification-free detection of non-coding RNAs. Nature Nanotechnology. 17(10). 1120–1126. 173 indexed citations breakdown →
8.
Kaminski, Michael M., Omar O. Abudayyeh, Jonathan S. Gootenberg, Feng Zhang, & James J. Collins. (2021). CRISPR-based diagnostics. Nature Biomedical Engineering. 5(7). 643–656. 823 indexed citations breakdown →
9.
Naert, Thomas, Özgün Çiçek, Michael M. Kaminski, et al.. (2021). Deep learning is widely applicable to phenotyping embryonic development and disease. Development. 148(21). 21 indexed citations
10.
Kaminski, Michael M., Miguel A. Alcantar, Isadora T. Lape, et al.. (2020). A CRISPR-based assay for the detection of opportunistic infections post-transplantation and for the monitoring of transplant rejection. Nature Biomedical Engineering. 4(6). 601–609. 89 indexed citations
11.
Lagies, Simon, Tillmann Bork, Michael M. Kaminski, et al.. (2019). Impact of Diabetic Stress Conditions on Renal Cell Metabolome. Cells. 8(10). 1141–1141. 8 indexed citations
12.
Lagies, Simon, et al.. (2018). Metabolic characterization of directly reprogrammed renal tubular epithelial cells (iRECs). Scientific Reports. 8(1). 3878–3878. 16 indexed citations
13.
Jansen, Katja, Miguel Castilho, Michael M. Kaminski, et al.. (2018). Fabrication of Kidney Proximal Tubule Grafts Using Biofunctionalized Electrospun Polymer Scaffolds. Macromolecular Bioscience. 19(2). e1800412–e1800412. 24 indexed citations
14.
Kaminski, Michael M., et al.. (2017). Engineering kidney cells: reprogramming and directed differentiation to renal tissues. Cell and Tissue Research. 369(1). 185–197. 11 indexed citations
15.
Kaminski, Michael M., et al.. (2017). Direct reprogramming of fibroblasts into renal tubular epithelial cells by defined transcription factors. Mechanisms of Development. 145. S95–S95. 61 indexed citations
16.
Kaminski, Michael M., Catena Kresbach, Hannes Engel, et al.. (2016). Direct reprogramming of fibroblasts into renal tubular epithelial cells by defined transcription factors. Nature Cell Biology. 18(12). 1269–1280. 99 indexed citations
17.
Kaminski, Michael M., Annette Ohnemus, Peter Staeheli, & Dennis Rubbenstroth. (2012). Pandemic 2009 H1N1 Influenza A Virus Carrying a Q136K Mutation in the Neuraminidase Gene Is Resistant to Zanamivir but Exhibits Reduced Fitness in the Guinea Pig Transmission Model. Journal of Virology. 87(3). 1912–1915. 21 indexed citations
18.
Kaminski, Michael M., et al.. (2011). Plasmacytoid dendritic cells and Toll-like receptor 7-dependent signalling promote efficient protection of mice against highly virulent influenza A virus. Journal of General Virology. 93(3). 555–559. 30 indexed citations
19.
Seibert, Christopher W., Michael M. Kaminski, Dennis Rubbenstroth, et al.. (2010). Oseltamivir-Resistant Variants of the 2009 Pandemic H1N1 Influenza A Virus Are Not Attenuated in the Guinea Pig and Ferret Transmission Models. Journal of Virology. 84(21). 11219–11226. 85 indexed citations
20.
Pałasz, Artur & Michael M. Kaminski. (2009). Stem cell niche in the Drosophila ovary and testis; a valuable model of the intercellular signalling relationships. Advances in Medical Sciences. 54(2). 143–9. 5 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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