Tin Phan
Impact in
- Modeling and Simulation top 5%
- Mathematical Biology Tumor Growth
- COVID-19 epidemiological studies
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- MicroRNA in disease regulation
- Cancer-related molecular mechanisms research
Papers in
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- Mathematical Biology Tumor Growth 5
- COVID-19 epidemiological studies 4
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- Prostate Cancer Treatment and Research 6
- Co-authors
- Yang Kuang (18 shared papers)John G. Clohessy (1 shared paper)Limei Wang (1 shared paper)Tuan M. Nguyen (1 shared paper)Xiao‐Ou Zhang (1 shared paper)Pier Paolo Pandolfi (1 shared paper)Yang Zhang (1 shared paper)Eric J. Kostelich (3 shared papers)
- Journals
- Applied Sciences (4 papers)PLoS Pathogens (2 papers)Mathematical Biosciences & Engineering (2 papers)Proceedings of the National Academy of Sciences (2 papers)Scientific Reports (1 paper)
- Partner nations
- United StatesSwedenFrance
In The Last Decade
Tin Phan
27 papers receiving 352 citations
Peers
Comparison fields: 5 of 82
- Modeling and Simulation 77
- Cancer Research 106
- Infectious Diseases 56
- Molecular Biology 149
- Virology 9
Countries citing papers authored by Tin Phan
This map shows the geographic impact of Tin Phan'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 Tin Phan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Tin Phan more than expected).
Fields of papers citing papers by Tin Phan
This network shows the impact of papers produced by Tin Phan. 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 Tin Phan. The network helps show where Tin Phan may publish in the future.
Co-authors
The 25 scholars most cited alongside Tin Phan, 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 29 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2021 | 113 | |
| 2 | 2022 | 39 | |
| 3 | 2022 | 31 | |
| 4 | 2020 | 30 | |
| 5 | 2019 | 22 | |
| 6 | 2018 | 12 | |
| 7 | 2023 | 11 | |
| 8 | 2018 | 10 | |
| 9 | Sandy soils in south central coastal Vietnam: their origin, constraints and management | 2010 | 10 |
| 10 | 2023 | 8 | |
| 11 | 2024 | 8 | |
| 12 | 2023 | 7 | |
| 13 | 2020 | 6 | |
| 14 | 2021 | 6 | |
| 15 | 2024 | 6 | |
| 16 | 2020 | 6 | |
| 17 | 2024 | 5 | |
| 18 | 2021 | 5 | |
| 19 | 2018 | 4 | |
| 20 | 2023 | 3 |
About Tin Phan
Tin Phan is a scholar working on Modeling and Simulation, Pulmonary and Respiratory Medicine, Infectious Diseases, Genetics and Cancer Research, having authored 29 papers that have together received 358 indexed citations. Recurring topics across this work include Prostate Cancer Treatment and Research (6 papers), SARS-CoV-2 and COVID-19 Research (5 papers), Mathematical Biology Tumor Growth (5 papers), SARS-CoV-2 detection and testing (4 papers), COVID-19 Clinical Research Studies (4 papers), Evolution and Genetic Dynamics (4 papers), Cancer Genomics and Diagnostics (4 papers) and COVID-19 epidemiological studies (4 papers). The work is most often cited by research in Modeling and Simulation (77 citations), Cancer Research (106 citations), Infectious Diseases (56 citations), Molecular Biology (149 citations) and Virology (9 citations). Tin Phan has collaborated with scholars based in United States, Sweden and France. Frequent co-authors include Yang Kuang, John G. Clohessy, Limei Wang, Tuan M. Nguyen, Xiao‐Ou Zhang, Pier Paolo Pandolfi, Yang Zhang, Eric J. Kostelich, Bruce Pell and Fuqing Wu. Their work appears in journals such as Applied Sciences, PLoS Pathogens, Mathematical Biosciences & Engineering, Proceedings of the National Academy of Sciences and Scientific Reports.
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.