Chia‐Lin Chen
Impact in
- Cancer Research top 5%
- Cancer, Hypoxia, and Metabolism
- Cancer, Lipids, and Metabolism
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- Tea Polyphenols and Effects
Papers in
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- Cancer, Hypoxia, and Metabolism 7
- Co-authors
- Keigo Machida (10 shared papers)Vasu Punj (5 shared papers)Yung‐Hsi Kao (2 shared papers)Linda Sher (4 shared papers)Hsing-Jien Kung (3 shared papers)David K. Ann (3 shared papers)Yun Yen (3 shared papers)Sheng-Chieh Hsu (3 shared papers)
- Journals
- Nature Communications (3 papers)Hepatology (2 papers)Molecular Nutrition & Food Research (2 papers)Medical Physics (1 paper)Assay and Drug Development Technologies (1 paper)
- Partner nations
- TaiwanUnited StatesJapan
In The Last Decade
Chia‐Lin Chen
41 papers receiving 2.0k citations
Chia‐Lin Chen's Hit Papers
Peers
Comparison fields: 5 of 121
- Cancer Research 430
- Pathology and Forensic Medicine 342
- Biochemistry 118
- Hepatology 135
- Biological Psychiatry 33
Countries citing papers authored by Chia‐Lin Chen
This map shows the geographic impact of Chia‐Lin Chen'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 Chia‐Lin Chen with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Chia‐Lin Chen more than expected).
Fields of papers citing papers by Chia‐Lin Chen
This network shows the impact of papers produced by Chia‐Lin Chen. 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 Chia‐Lin Chen. The network helps show where Chia‐Lin Chen may publish in the future.
Co-authors
The 25 scholars most cited alongside Chia‐Lin Chen, 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 41 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2015 | 318 | |
| 2 | 2006 | 259 | |
| 3 | Arginine Signaling and Cancer Metabolism Hit paper breakdown → | 2021 | 183 |
| 4 | 2005 | 110 | |
| 5 | 2014 | 91 | |
| 6 | 2015 | 91 | |
| 7 | 2021 | 83 | |
| 8 | 2011 | 70 | |
| 9 | 2009 | 66 | |
| 10 | 2011 | 63 | |
| 11 | 2015 | 57 | |
| 12 | 2015 | 54 | |
| 13 | 1996 | 41 | |
| 14 | 2021 | 39 | |
| 15 | 2021 | 39 | |
| 16 | 2012 | 38 | |
| 17 | 2012 | 38 | |
| 18 | 2017 | 34 | |
| 19 | 2003 | 33 | |
| 20 | 2014 | 26 |
About Chia‐Lin Chen
Chia‐Lin Chen is a scholar working on Molecular Biology, Cancer Research, Oncology, Radiology, Nuclear Medicine and Imaging and Genetics, having authored 41 papers that have together received 2.0k indexed citations. Recurring topics across this work include Cancer, Hypoxia, and Metabolism (7 papers), Medical Imaging Techniques and Applications (6 papers), Cancer Cells and Metastasis (5 papers), Pancreatic function and diabetes (3 papers), Virus-based gene therapy research (3 papers), Cancer-related Molecular Pathways (3 papers), Tea Polyphenols and Effects (3 papers) and Diabetes and associated disorders (2 papers). The work is most often cited by research in Cancer Research (430 citations), Pathology and Forensic Medicine (342 citations), Biochemistry (118 citations), Hepatology (135 citations) and Biological Psychiatry (33 citations). Chia‐Lin Chen has collaborated with scholars based in Taiwan, United States and Japan. Frequent co-authors include Keigo Machida, Vasu Punj, Yung‐Hsi Kao, Linda Sher, Hsing-Jien Kung, David K. Ann, Yun Yen, Sheng-Chieh Hsu, Stanley M. Tahara and Jun Xu. Their work appears in journals such as Nature Communications, Hepatology, Molecular Nutrition & Food Research, Medical Physics and Assay and Drug Development Technologies.
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.