Nicolas Städler
Impact in
- Statistics and Probability top 5%
- Statistical Methods and Inference
- Statistical Methods and Bayesian Inference
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- Neurogenesis and neuroplasticity mechanisms
Papers in
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- Statistical Methods and Inference 4
- Statistical Methods and Bayesian Inference 3
- Statistical Methods in Clinical Trials 3
- Oncology 5
- Cancer Immunotherapy and Biomarkers 3
- Co-authors
- Peter Bühlmann (3 shared papers)Zherui Wu (3 shared papers)Patricia Forgez (4 shared papers)E. Segal (2 shared papers)Diane Damotte (1 shared paper)Marco Alifano (1 shared paper)Jean Trédaniel (1 shared paper)Filippo Lococo (1 shared paper)
- Journals
- Cancer Letters (2 papers)Clinical Cancer Research (1 paper)Journal of Neuroinflammation (1 paper)Journal of Medicinal Chemistry (1 paper)Advances in Therapy (1 paper)
- Partner nations
- SwitzerlandFranceUnited Kingdom
In The Last Decade
Nicolas Städler
18 papers receiving 438 citations
Peers
Comparison fields: 5 of 95
- Statistics and Probability 64
- Developmental Neuroscience 29
- Oncology 134
- Immunology 61
- Cancer Research 32
Countries citing papers authored by Nicolas Städler
This map shows the geographic impact of Nicolas Städler'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 Nicolas Städler with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Nicolas Städler more than expected).
Fields of papers citing papers by Nicolas Städler
This network shows the impact of papers produced by Nicolas Städler. 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 Nicolas Städler. The network helps show where Nicolas Städler may publish in the future.
Co-authors
The 25 scholars most cited alongside Nicolas Städler, 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 | 2019 | 178 | |
| 2 | 2010 | 53 | |
| 3 | 2011 | 45 | |
| 4 | 2016 | 29 | |
| 5 | 2005 | 22 | |
| 6 | 2020 | 19 | |
| 7 | 2014 | 14 | |
| 8 | 2022 | 14 | |
| 9 | 2016 | 13 | |
| 10 | 2017 | 11 | |
| 11 | 2014 | 11 | |
| 12 | 2016 | 8 | |
| 13 | 2010 | 8 | |
| 14 | 2021 | 8 | |
| 15 | 2023 | 4 | |
| 16 | 2007 | 4 | |
| 17 | 2024 | 2 | |
| 18 | 2025 | 2 | |
| 19 | 2025 | 0 |
About Nicolas Städler
Nicolas Städler is a scholar working on Statistics and Probability, Oncology, Molecular Biology, Artificial Intelligence and Immunology, having authored 19 papers that have together received 445 indexed citations. Recurring topics across this work include Statistical Methods and Inference (4 papers), Bayesian Methods and Mixture Models (4 papers), Cancer Immunotherapy and Biomarkers (3 papers), Statistical Methods and Bayesian Inference (3 papers), Statistical Methods in Clinical Trials (3 papers), Immunotherapy and Immune Responses (2 papers), Bioinformatics and Genomic Networks (2 papers) and Diabetes Management and Research (1 paper). The work is most often cited by research in Statistics and Probability (64 citations), Developmental Neuroscience (29 citations), Oncology (134 citations), Immunology (61 citations) and Cancer Research (32 citations). Nicolas Städler has collaborated with scholars based in Switzerland, France and United Kingdom. Frequent co-authors include Peter Bühlmann, Zherui Wu, Patricia Forgez, E. Segal, Diane Damotte, Marco Alifano, Jean Trédaniel, Filippo Lococo, Ludovic Fournel and Antonio Bobbio. Their work appears in journals such as Cancer Letters, Clinical Cancer Research, Journal of Neuroinflammation, Journal of Medicinal Chemistry and Advances in Therapy.
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.