Su Phyu
Impact in
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- CAR-T cell therapy research
- Cancer Immunotherapy and Biomarkers
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- Immunotherapy and Immune Responses
- Immune Cell Function and Interaction
- Immune cells in cancer
Papers in
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- Metabolomics and Mass Spectrometry Studies 3
- Metabolism, Diabetes, and Cancer 2
- PI3K/AKT/mTOR signaling in cancer 2
- Oncology 6
- CAR-T cell therapy research 5
- Co-authors
- Timothy Smith (8 shared papers)Hideho Okada (8 shared papers)Ian N. Fleming (2 shared papers)Chih‐Chung Tseng (3 shared papers)Marco Gallus (3 shared papers)Akane Yamamichi (6 shared papers)Eileen E. Parkes (2 shared papers)John de Groot (1 shared paper)
- Journals
- Neuro-Oncology (2 papers)Magnetic Resonance Materials in Physics Biology and Medicine (1 paper)Pharmaceuticals (1 paper)Neuro-Oncology Advances (1 paper)Investigational New Drugs (1 paper)
- Partner nations
- United StatesUnited KingdomUkraine
In The Last Decade
Su Phyu
19 papers receiving 262 citations
Peers
Comparison fields: 5 of 50
- Oncology 126
- Immunology 70
- Cancer Research 38
- Genetics 21
- Molecular Biology 103
Countries citing papers authored by Su Phyu
This map shows the geographic impact of Su Phyu'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 Su Phyu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Su Phyu more than expected).
Fields of papers citing papers by Su Phyu
This network shows the impact of papers produced by Su Phyu. 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 Su Phyu. The network helps show where Su Phyu may publish in the future.
Co-authors
The 25 scholars most cited alongside Su Phyu, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2020 | 51 | |
| 2 | 2024 | 40 | |
| 3 | 2024 | 32 | |
| 4 | 2021 | 27 | |
| 5 | 2024 | 25 | |
| 6 | Effects of Administered Cardioprotective Drugs on Treatment Response of Breast Cancer Cells. | 2016 | 19 |
| 7 | 2016 | 16 | |
| 8 | 2016 | 15 | |
| 9 | 2015 | 13 | |
| 10 | 2018 | 9 | |
| 11 | 2018 | 7 | |
| 12 | 2024 | 4 | |
| 13 | 2024 | 4 | |
| 14 | 2025 | 3 | |
| 15 | 2025 | 1 | |
| 16 | 2017 | 1 | |
| 17 | 2023 | 1 | |
| 18 | 2023 | 1 | |
| 19 | 2016 | 1 | |
| 20 | 2023 | 0 |
About Su Phyu
Su Phyu is a scholar working on Molecular Biology, Oncology, Immunology, Cancer Research and Neurology, having authored 20 papers that have together received 270 indexed citations. Recurring topics across this work include CAR-T cell therapy research (5 papers), Metabolomics and Mass Spectrometry Studies (3 papers), Immune cells in cancer (3 papers), Cancer, Lipids, and Metabolism (2 papers), Metabolism, Diabetes, and Cancer (2 papers), Neuroinflammation and Neurodegeneration Mechanisms (2 papers), Immune Cell Function and Interaction (2 papers) and PI3K/AKT/mTOR signaling in cancer (2 papers). The work is most often cited by research in Oncology (126 citations), Immunology (70 citations), Cancer Research (38 citations), Genetics (21 citations) and Molecular Biology (103 citations). Su Phyu has collaborated with scholars based in United States, United Kingdom and Ukraine. Frequent co-authors include Timothy Smith, Hideho Okada, Ian N. Fleming, Chih‐Chung Tseng, Marco Gallus, Akane Yamamichi, Eileen E. Parkes, John de Groot, Tiffany Chen and David A. Scheiblin. Their work appears in journals such as Neuro-Oncology, Magnetic Resonance Materials in Physics Biology and Medicine, Pharmaceuticals, Neuro-Oncology Advances and Investigational New Drugs.
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.