Maria Schwaederlé
- Cancer Research top 1%
- Cancer Genomics and Diagnostics 31
- Oncology top 2%
- Cancer-related Molecular Pathways 6
- Colorectal Cancer Treatments and Studies 4
- CAR-T cell therapy research 3
- Lung Cancer Research Studies 3
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- Genetic factors in colorectal cancer 7
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- Lung Cancer Treatments and Mutations 15
- Genetics top 5%
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- Statistical Methods in Clinical Trials 6
- Co-authors
- Razelle KurzrockJ. Jack LeePaul T. FantaVladimir LazarDavid PiccioniRichard L. SchilskyJohn MendelsohnDavid Arguello
- Partner nations
- United StatesNetherlandsBrazil
In The Last Decade
Maria Schwaederlé
43 papers receiving 3.1k citations
Hit Papers
Peers
Comparison fields: 5 of 115
- Cancer Research 1.7k
- Oncology 1.5k
- Pathology and Forensic Medicine 611
- Pulmonary and Respiratory Medicine 1.1k
- Genetics 206
Countries citing papers authored by Maria Schwaederlé
This map shows the geographic impact of Maria Schwaederlé'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 Maria Schwaederlé with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Maria Schwaederlé more than expected).
Fields of papers citing papers by Maria Schwaederlé
This network shows the impact of papers produced by Maria Schwaederlé. 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 Maria Schwaederlé. The network helps show where Maria Schwaederlé may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Maria Schwaederlé, 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 | Molecular profiling of cancer patients enables personalized combination therapy: the I-PREDICT studybreakdown → | 2019 | 429 |
| 2 | 2018 | 38 | |
| 3 | 2018 | 5 | |
| 4 | 2017 | 118 | |
| 5 | 2017 | 89 | |
| 6 | 2017 | 57 | |
| 7 | 2016 | 34 | |
| 8 | 2016 | 102 | |
| 9 | 2016 | 125 | |
| 10 | 2016 | 25 | |
| 11 | 2016 | 235 | |
| 12 | 2015 | 96 | |
| 13 | 2015 | 71 | |
| 14 | 2015 | 138 | |
| 15 | 2015 | 103 | |
| 16 | 2015 | 8 | |
| 17 | 2015 | 2 | |
| 18 | 2015 | 8 | |
| 19 | 2014 | 1 | |
| 20 | 2012 | 58 |
About Maria Schwaederlé
Maria Schwaederlé is a scholar working on Cancer Research, Oncology and Statistics and Probability, having authored 43 papers that have together received 3.2k indexed citations. Recurring topics across this work include Cancer Genomics and Diagnostics (31 papers), Lung Cancer Treatments and Mutations (15 papers), Genetic factors in colorectal cancer (7 papers), Cancer-related Molecular Pathways (6 papers), Statistical Methods in Clinical Trials (6 papers), Colorectal Cancer Treatments and Studies (4 papers), CAR-T cell therapy research (3 papers) and Lung Cancer Research Studies (3 papers). The work is most often cited by research in Cancer Research (1.7k citations), Oncology (1.5k citations) and Pathology and Forensic Medicine (611 citations). Maria Schwaederlé has collaborated with scholars based in United States, Netherlands and Brazil. Frequent co-authors include Razelle Kurzrock, J. Jack Lee, Paul T. Fanta, Vladimir Lazar, David Piccioni, Richard L. Schilsky, John Mendelsohn, David Arguello, Melissa Zhao and Zoran Gatalica. Their work appears in journals such as Nature Medicine, Journal of Clinical Oncology and Blood.
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.