Stephan Gade
Impact in
- Cancer Research top 5%
- MicroRNA in disease regulation
- Cancer-related molecular mechanisms research
- Molecular Biology top 10%
- Circular RNAs in diseases
- Bioinformatics and Genomic Networks
- Gene expression and cancer classification
Papers in
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- Circular RNAs in diseases 3
- Advanced Biosensing Techniques and Applications 3
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- Cancer Genomics and Diagnostics 3
- MicroRNA in disease regulation 3
- Cancer-related molecular mechanisms research 2
- Co-authors
- Marcus Bantscheff (3 shared papers)Jan C. Brase (8 shared papers)Carola Doce (1 shared paper)Mikhail M. Savitski (1 shared paper)Holger Franken (1 shared paper)Dorothee Childs (1 shared paper)Wolfgang Huber (1 shared paper)Gerard Drewes (1 shared paper)
In The Last Decade
Stephan Gade
20 papers receiving 1.2k citations
Stephan Gade's Hit Papers
Peers
Comparison fields: 5 of 100
- Cancer Research 281
- Molecular Biology 791
- Spectroscopy 173
- Cell Biology 84
- Computational Theory and Mathematics 83
Countries citing papers authored by Stephan Gade
This map shows the geographic impact of Stephan Gade'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 Stephan Gade with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Stephan Gade more than expected).
Fields of papers citing papers by Stephan Gade
This network shows the impact of papers produced by Stephan Gade. 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 Stephan Gade. The network helps show where Stephan Gade may publish in the future.
Co-authors
The 25 scholars most cited alongside Stephan Gade, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | Thermal proteome profiling for unbiased identification of direct and indirect drug targets using multiplexed quantitative mass spectrometry Hit paper breakdown → | 2015 | 463 |
| 2 | 2012 | 123 | |
| 3 | 2014 | 103 | |
| 4 | 2011 | 93 | |
| 5 | 2010 | 78 | |
| 6 | 2013 | 64 | |
| 7 | 2010 | 51 | |
| 8 | 2013 | 40 | |
| 9 | 2017 | 36 | |
| 10 | 2011 | 36 | |
| 11 | 2012 | 25 | |
| 12 | 2010 | 15 | |
| 13 | 2012 | 13 | |
| 14 | 2014 | 11 | |
| 15 | 2014 | 7 | |
| 16 | 2014 | 4 | |
| 17 | 2015 | 3 | |
| 18 | 2024 | 2 | |
| 19 | 2013 | 1 | |
| 20 | 2015 | 1 |
About Stephan Gade
Stephan Gade is a scholar working on Molecular Biology, Cancer Research, Oncology, Pulmonary and Respiratory Medicine and Genetics, having authored 20 papers that have together received 1.2k indexed citations. Recurring topics across this work include Cancer Genomics and Diagnostics (3 papers), Circular RNAs in diseases (3 papers), Advanced Biosensing Techniques and Applications (3 papers), HER2/EGFR in Cancer Research (3 papers), MicroRNA in disease regulation (3 papers), Advanced Proteomics Techniques and Applications (2 papers), Advanced Breast Cancer Therapies (2 papers) and Cancer-related molecular mechanisms research (2 papers). The work is most often cited by research in Cancer Research (281 citations), Molecular Biology (791 citations), Spectroscopy (173 citations), Cell Biology (84 citations) and Computational Theory and Mathematics (83 citations). Stephan Gade has collaborated with scholars based in Germany, Belgium and Australia. Frequent co-authors include Marcus Bantscheff, Jan C. Brase, Carola Doce, Mikhail M. Savitski, Holger Franken, Dorothee Childs, Wolfgang Huber, Gerard Drewes, Holger Sültmann and Toby Mathieson. Their work appears in journals such as Bioinformatics, Cancer Research, Journal of Clinical Oncology, Nature Protocols and Journal of Molecular Medicine.
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.