Philipp Ottis
Impact in
- Hematology top 10%
- Multiple Myeloma Research and Treatments
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- Protein Degradation and Inhibitors
- Ubiquitin and proteasome pathways
- Histone Deacetylase Inhibitors Research
- Phosphodiesterase function and regulation
- Prion Diseases and Protein Misfolding
Papers in
-
- Protein Degradation and Inhibitors 4
- Ubiquitin and proteasome pathways 4
- Receptor Mechanisms and Signaling 3
- Phosphodiesterase function and regulation 3
- Mitochondrial Function and Pathology 2
- Machine Learning in Bioinformatics 1
- Oncology 2
- Peptidase Inhibition and Analysis 2
- Co-authors
- Craig M. Crews (3 shared papers)Philipp M. Cromm (2 shared papers)Momar Toure (2 shared papers)Jeffrey L. Gustafson (1 shared paper)Carsten Korth (8 shared papers)Eunhwa Ko (1 shared paper)Hans Kretzschmar (2 shared papers)Verian Bader (4 shared papers)
- Journals
- ACS Chemical Biology (3 papers)Journal of Visualized Experiments (2 papers)PLoS ONE (2 papers)Molecular Neurobiology (1 paper)Biological Psychiatry (1 paper)
- Partner nations
- GermanyUnited StatesNetherlands
In The Last Decade
Philipp Ottis
14 papers receiving 666 citations
Peers
Comparison fields: 5 of 64
- Hematology 144
- Molecular Biology 593
- Aging 13
- Oncology 200
- Biological Psychiatry 12
Countries citing papers authored by Philipp Ottis
This map shows the geographic impact of Philipp Ottis'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 Philipp Ottis with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Philipp Ottis more than expected).
Fields of papers citing papers by Philipp Ottis
This network shows the impact of papers produced by Philipp Ottis. 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 Philipp Ottis. The network helps show where Philipp Ottis may publish in the future.
Co-authors
The 25 scholars most cited alongside Philipp Ottis, 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 | 2017 | 184 | |
| 2 | 2017 | 133 | |
| 3 | 2019 | 107 | |
| 4 | 2011 | 59 | |
| 5 | 2014 | 43 | |
| 6 | 2012 | 42 | |
| 7 | 2014 | 33 | |
| 8 | 2018 | 32 | |
| 9 | 2012 | 23 | |
| 10 | 2013 | 11 | |
| 11 | 2012 | 11 | |
| 12 | 2012 | 2 | |
| 13 | 2013 | 2 | |
| 14 | 2017 | 1 |
About Philipp Ottis
Philipp Ottis is a scholar working on Molecular Biology, Oncology, Cell Biology, Physiology and Aging, having authored 14 papers that have together received 683 indexed citations. Recurring topics across this work include Protein Degradation and Inhibitors (4 papers), Ubiquitin and proteasome pathways (4 papers), Receptor Mechanisms and Signaling (3 papers), Phosphodiesterase function and regulation (3 papers), Genetics, Aging, and Longevity in Model Organisms (2 papers), Mitochondrial Function and Pathology (2 papers), Peptidase Inhibition and Analysis (2 papers) and Machine Learning in Bioinformatics (1 paper). The work is most often cited by research in Hematology (144 citations), Molecular Biology (593 citations), Aging (13 citations), Oncology (200 citations) and Biological Psychiatry (12 citations). Philipp Ottis has collaborated with scholars based in Germany, United States and Netherlands. Frequent co-authors include Craig M. Crews, Philipp M. Cromm, Momar Toure, Jeffrey L. Gustafson, Carsten Korth, Eunhwa Ko, Hans Kretzschmar, Verian Bader, Filip Roudnicky and Phillip Thienger. Their work appears in journals such as ACS Chemical Biology, Journal of Visualized Experiments, PLoS ONE, Molecular Neurobiology and Biological Psychiatry.
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.