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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- Cancer Genomics and Diagnostics 19
- Co-authors
- Franziska Michor (14 shared papers)George Em Karniadakis (5 shared papers)Kevin Leder (26 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 (9 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 StatesIcelandNorway
In The Last Decade
Jasmine Foo
52 papers receiving 1.7k citations
Peers
Comparison fields: 5 of 125
- Modeling and Simulation 354
- Statistics, Probability and Uncertainty 332
- Cancer Research 495
- Oncology 294
- 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 52 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2014 | 188 | |
| 2 | 2008 | 168 | |
| 3 | 2009 | 162 | |
| 4 | 2011 | 97 | |
| 5 | 2009 | 92 | |
| 6 | 2012 | 69 | |
| 7 | 2012 | 66 | |
| 8 | 2005 | 65 | |
| 9 | 2009 | 63 | |
| 10 | 2015 | 61 | |
| 11 | 2016 | 51 | |
| 12 | 2009 | 47 | |
| 13 | 2020 | 46 | |
| 14 | 2011 | 44 | |
| 15 | 2020 | 43 | |
| 16 | 2011 | 42 | |
| 17 | 2011 | 42 | |
| 18 | 2012 | 31 | |
| 19 | 2007 | 31 | |
| 20 | 2019 | 29 |
About Jasmine Foo
Jasmine Foo is a scholar working on Cancer Research, Molecular Biology, Modeling and Simulation, Genetics and Pulmonary and Respiratory Medicine, having authored 52 papers that have together received 1.7k indexed citations. Recurring topics across this work include Cancer Genomics and Diagnostics (19 papers), Mathematical Biology Tumor Growth (16 papers), Evolution and Genetic Dynamics (10 papers), Chronic Myeloid Leukemia Treatments (6 papers), Lung Cancer Treatments and Mutations (6 papers), Probabilistic and Robust Engineering Design (5 papers), Cancer Cells and Metastasis (4 papers) and Wind and Air Flow Studies (4 papers). The work is most often cited by research in Modeling and Simulation (354 citations), Statistics, Probability and Uncertainty (332 citations), Cancer Research (495 citations), Oncology (294 citations) and Computational Mathematics (7 citations). Jasmine Foo has collaborated with scholars based in United States, Iceland and Norway. Frequent co-authors include Franziska Michor, George Em Karniadakis, Kevin Leder, Xiaoliang Wan, Shannon M. Mumenthaler, William Pao, Didier Lucor, Parag Mallick, John Mayberry 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.