Tin Phan
Impact in
- Modeling and Simulation top 5%
- Mathematical Biology Tumor Growth
- COVID-19 epidemiological studies
-
- 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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- SARS-CoV-2 and COVID-19 Research 4
- SARS-CoV-2 detection and testing 4
- COVID-19 Clinical Research Studies 4
- Co-authors
- Yang Kuang (19 shared papers)Limei Wang (1 shared paper)Xiao‐Ou Zhang (1 shared paper)Yang Zhang (1 shared paper)Tuan M. Nguyen (1 shared paper)John G. Clohessy (1 shared paper)Pier Paolo Pandolfi (1 shared paper)Eric J. Kostelich (3 shared papers)
- Journals
- Applied Sciences (4 papers)Proceedings of the National Academy of Sciences (2 papers)PLoS Pathogens (2 papers)Mathematical Biosciences & Engineering (2 papers)Life (1 paper)
- Partner nations
- United StatesChinaFrance
In The Last Decade
Tin Phan
29 papers receiving 393 citations
Peers
Comparison fields: 5 of 81
- Modeling and Simulation 79
- Cancer Research 105
- Infectious Diseases 67
- Molecular Biology 154
- Virology 10
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 | 120 | |
| 2 | 2022 | 41 | |
| 3 | 2020 | 32 | |
| 4 | 2022 | 32 | |
| 5 | 2019 | 22 | |
| 6 | 2024 | 13 | |
| 7 | 2023 | 13 | |
| 8 | 2018 | 13 | |
| 9 | 2018 | 11 | |
| 10 | Sandy soils in south central coastal Vietnam: their origin, constraints and management | 2010 | 10 |
| 11 | 2023 | 9 | |
| 12 | 2023 | 9 | |
| 13 | 2024 | 8 | |
| 14 | 2016 | 8 | |
| 15 | 2024 | 7 | |
| 16 | 2020 | 7 | |
| 17 | 2021 | 7 | |
| 18 | 2021 | 6 | |
| 19 | 2020 | 6 | |
| 20 | 2018 | 5 |
About Tin Phan
Tin Phan is a scholar working on Modeling and Simulation, Infectious Diseases, Pulmonary and Respiratory Medicine, Genetics and Cancer Research, having authored 29 papers that have together received 400 indexed citations. Recurring topics across this work include Prostate Cancer Treatment and Research (6 papers), Mathematical Biology Tumor Growth (5 papers), Cancer Genomics and Diagnostics (4 papers), COVID-19 epidemiological studies (4 papers), Evolution and Genetic Dynamics (4 papers), SARS-CoV-2 and COVID-19 Research (4 papers), SARS-CoV-2 detection and testing (4 papers) and COVID-19 Clinical Research Studies (4 papers). The work is most often cited by research in Modeling and Simulation (79 citations), Cancer Research (105 citations), Infectious Diseases (67 citations), Molecular Biology (154 citations) and Virology (10 citations). Tin Phan has collaborated with scholars based in United States, China and France. Frequent co-authors include Yang Kuang, Limei Wang, Xiao‐Ou Zhang, Yang Zhang, Tuan M. Nguyen, John G. Clohessy, Pier Paolo Pandolfi, Eric J. Kostelich, Bruce Pell and Sharon Crook. Their work appears in journals such as Applied Sciences, Proceedings of the National Academy of Sciences, PLoS Pathogens, Mathematical Biosciences & Engineering and Life.
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.