Jasmine Foo
Impact in
- Modeling and Simulation top 0.5%
- Mathematical Biology Tumor Growth
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- Probabilistic and Robust Engineering Design
Papers in ⓘ
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- Mathematical Biology Tumor Growth 15
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- Cancer Genomics and Diagnostics 18
- Co-authors
- Franziska Michor (14 shared papers)George Em Karniadakis (5 shared papers)Kevin Leder (24 shared papers)Xiaoliang Wan (1 shared paper)Shannon M. Mumenthaler (11 shared papers)William Pao (4 shared papers)Didier Lucor (1 shared paper)Parag Mallick (4 shared papers)
- Journals
- PLoS Computational Biology (8 papers)Journal of Theoretical Biology (4 papers)Journal of Computational Physics (3 papers)npj Systems Biology and Applications (3 papers)JCO Clinical Cancer Informatics (2 papers)
- Partner nations
- United StatesIcelandJapan
In The Last Decade
Jasmine Foo
50 papers receiving 1.6k citations
Peers
Comparison fields: 5 of 128
- Modeling and Simulation 348
- Statistics, Probability and Uncertainty 331
- Cancer Research 530
- Oncology 331
- Computational Mathematics 7
Countries citing papers authored by Jasmine Foo
This map shows the geographic impact of Jasmine Foo'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 Jasmine Foo with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jasmine Foo more than expected).
Fields of papers citing papers by Jasmine Foo
This network shows the impact of papers produced by Jasmine Foo. 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 Jasmine Foo. The network helps show where Jasmine Foo may publish in the future.
Co-authors
The 25 scholars most cited alongside Jasmine Foo, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 50 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2014 | 188 | |
| 2 | 2008 | 168 | |
| 3 | 2009 | 161 | |
| 4 | 2011 | 97 | |
| 5 | 2009 | 92 | |
| 6 | 2012 | 66 | |
| 7 | 2012 | 66 | |
| 8 | 2005 | 65 | |
| 9 | 2009 | 62 | |
| 10 | 2015 | 61 | |
| 11 | 2016 | 49 | |
| 12 | 2009 | 47 | |
| 13 | 2011 | 44 | |
| 14 | 2020 | 42 | |
| 15 | 2011 | 42 | |
| 16 | 2011 | 42 | |
| 17 | 2020 | 41 | |
| 18 | 2012 | 31 | |
| 19 | 2007 | 30 | |
| 20 | 2019 | 27 |
About Jasmine Foo
Jasmine Foo is a scholar working on Modeling and Simulation, Cancer Research, Statistics, Probability and Uncertainty, Hematology and Genetics, having authored 50 papers that have together received 1.7k indexed citations. Recurring topics across this work include Cancer Genomics and Diagnostics (18 papers), Mathematical Biology Tumor Growth (15 papers), Evolution and Genetic Dynamics (9 papers), Lung Cancer Treatments and Mutations (7 papers), Chronic Myeloid Leukemia Treatments (6 papers), Probabilistic and Robust Engineering Design (5 papers), Chronic Lymphocytic Leukemia Research (4 papers) and Cancer Cells and Metastasis (4 papers). The work is most often cited by research in Modeling and Simulation (348 citations), Statistics, Probability and Uncertainty (331 citations), Cancer Research (530 citations), Oncology (331 citations) and Computational Mathematics (7 citations). Jasmine Foo has collaborated with scholars based in United States, Iceland and Japan. Frequent co-authors include Franziska Michor, George Em Karniadakis, Kevin Leder, Xiaoliang Wan, Shannon M. Mumenthaler, William Pao, Didier Lucor, Parag Mallick, Rick Durrett and David B. Agus. Their work appears in journals such as PLoS Computational Biology, Journal of Theoretical Biology, Journal of Computational Physics, npj Systems Biology and Applications and JCO Clinical Cancer Informatics.
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.