Stephanie Dauth
Impact in
- Neurology top 5%
- Barrier Structure and Function Studies
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- Neuroscience and Neural Engineering
Papers in
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- Bone Metabolism and Diseases 4
- S100 Proteins and Annexins 2
- Co-authors
- Kevin Kit Parker (9 shared papers)Ben M. Maoz (5 shared papers)Donald E. Ingber (3 shared papers)Anna Herland (3 shared papers)Thomas Grevesse (4 shared papers)Matthew A. Hemphill (2 shared papers)Sean P. Sheehy (4 shared papers)Bogdan Budnik (3 shared papers)
- Journals
- Biological Chemistry (2 papers)The Journal of Comparative Neurology (2 papers)Cardiovascular Pathology (1 paper)The FASEB Journal (1 paper)Annual Review of Pathology Mechanisms of Disease (1 paper)
- Partner nations
- GermanyUnited StatesSwitzerland
In The Last Decade
Stephanie Dauth
21 papers receiving 1.4k citations
Stephanie Dauth's Hit Papers
Peers
Comparison fields: 5 of 116
- Neurology 145
- Cellular and Molecular Neuroscience 275
- Biomedical Engineering 646
- Developmental Neuroscience 44
- Cell Biology 150
Countries citing papers authored by Stephanie Dauth
This map shows the geographic impact of Stephanie Dauth'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 Stephanie Dauth with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Stephanie Dauth more than expected).
Fields of papers citing papers by Stephanie Dauth
This network shows the impact of papers produced by Stephanie Dauth. 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 Stephanie Dauth. The network helps show where Stephanie Dauth may publish in the future.
Co-authors
The 25 scholars most cited alongside Stephanie Dauth, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 21 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | Engineered In Vitro Disease Models Hit paper breakdown → | 2015 | 421 |
| 2 | 2018 | 340 | |
| 3 | 2015 | 133 | |
| 4 | 2016 | 107 | |
| 5 | 2018 | 83 | |
| 6 | 2016 | 81 | |
| 7 | 2011 | 44 | |
| 8 | 2013 | 42 | |
| 9 | 2010 | 33 | |
| 10 | 2011 | 15 | |
| 11 | 2011 | 12 | |
| 12 | 2020 | 11 | |
| 13 | 2012 | 10 | |
| 14 | 2014 | 9 | |
| 15 | 2019 | 9 | |
| 16 | 2016 | 6 | |
| 17 | 2016 | 5 | |
| 18 | 2024 | 2 | |
| 19 | 2024 | 1 | |
| 20 | 2023 | 1 |
About Stephanie Dauth
Stephanie Dauth is a scholar working on Molecular Biology, Cellular and Molecular Neuroscience, Immunology, Neurology and Cancer Research, having authored 21 papers that have together received 1.4k indexed citations. Recurring topics across this work include Bone Metabolism and Diseases (4 papers), Protease and Inhibitor Mechanisms (3 papers), 3D Printing in Biomedical Research (3 papers), S100 Proteins and Annexins (2 papers), Barrier Structure and Function Studies (2 papers), Thyroid Disorders and Treatments (2 papers), Connective tissue disorders research (2 papers) and Peptidase Inhibition and Analysis (2 papers). The work is most often cited by research in Neurology (145 citations), Cellular and Molecular Neuroscience (275 citations), Biomedical Engineering (646 citations), Developmental Neuroscience (44 citations) and Cell Biology (150 citations). Stephanie Dauth has collaborated with scholars based in Germany, United States and Switzerland. Frequent co-authors include Kevin Kit Parker, Ben M. Maoz, Donald E. Ingber, Anna Herland, Thomas Grevesse, Matthew A. Hemphill, Sean P. Sheehy, Bogdan Budnik, Chung Jong Yu and Borna E. Dabiri. Their work appears in journals such as Biological Chemistry, The Journal of Comparative Neurology, Cardiovascular Pathology, The FASEB Journal and Annual Review of Pathology Mechanisms of Disease.
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.