Maria Schwaederlé
- Cancer Research top 1%
- Oncology top 2%
- Pulmonary and Respiratory Medicine top 2%
- Molecular Biology top 10%
- Pathology and Forensic Medicine top 2%
- Co-authors
- Razelle KurzrockJ. Jack LeePaul T. FantaVladimir LazarDavid PiccioniRichard L. SchilskyJohn MendelsohnDavid Arguello
- Topics
- Cancer Genomics and Diagnostics (31 papers)Lung Cancer Treatments and Mutations (15 papers)Genetic factors in colorectal cancer (7 papers)
- 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
- Pulmonary and Respiratory Medicine 1.1k
- Molecular Biology 1.0k
- Pathology and Forensic Medicine 611
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 of co-authors of Maria Schwaederlé
This figure shows the co-authorship network connecting the top 25 collaborators of Maria Schwaederlé. A scholar is included among the top collaborators of Maria Schwaederlé based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Maria Schwaederlé. Maria Schwaederlé is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | Molecular profiling of cancer patients enables personalized combination therapy: the I-PREDICT studybreakdown → | 429 |
| 2 | 38 | |
| 3 | 5 | |
| 4 | 118 | |
| 5 | 89 | |
| 6 | 57 | |
| 7 | 34 | |
| 8 | 102 | |
| 9 | 125 | |
| 10 | 25 | |
| 11 | 235 | |
| 12 | 96 | |
| 13 | 71 | |
| 14 | 138 | |
| 15 | 103 | |
| 16 | 8 | |
| 17 | 2 | |
| 18 | 8 | |
| 19 | 1 | |
| 20 | 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) and Genetic factors in colorectal cancer (7 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.