Chun-Chin Chen
Impact in
- Oncology top 10%
- PARP inhibition in cancer therapy
Papers in
-
- CRISPR and Genetic Engineering 7
- DNA Repair Mechanisms 7
- Epigenetics and DNA Methylation 3
- TGF-β signaling in diseases 1
- Oncology 5
- PARP inhibition in cancer therapy 4
- Co-authors
- Maria Jasin (6 shared papers)Elizabeth M. Kass (3 shared papers)Weiran Feng (1 shared paper)Pei Xin Lim (1 shared paper)Franklin Chau‐Nan Hong (1 shared paper)Chih-Fu Yang (1 shared paper)Jin‐Yuh Shew (2 shared papers)Eva Y.-H.P. Lee (2 shared papers)
- Journals
- Leukemia (3 papers)Proceedings of the National Academy of Sciences (2 papers)Cancer Research (1 paper)Applied Surface Science (1 paper)Cell Reports (1 paper)
- Partner nations
- United StatesTaiwanBrazil
In The Last Decade
Chun-Chin Chen
18 papers receiving 853 citations
Peers
Comparison fields: 5 of 85
- Oncology 278
- Cancer Research 136
- Molecular Biology 560
- Biomaterials 91
- Aging 8
Countries citing papers authored by Chun-Chin Chen
This map shows the geographic impact of Chun-Chin 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 Chun-Chin Chen with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Chun-Chin Chen more than expected).
Fields of papers citing papers by Chun-Chin Chen
This network shows the impact of papers produced by Chun-Chin 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 Chun-Chin Chen. The network helps show where Chun-Chin Chen may publish in the future.
Co-authors
The 25 scholars most cited alongside Chun-Chin 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
| # | Work | ||
|---|---|---|---|
| 1 | 2017 | 216 | |
| 2 | 2012 | 115 | |
| 3 | 2004 | 108 | |
| 4 | 2004 | 79 | |
| 5 | 2013 | 78 | |
| 6 | 2016 | 63 | |
| 7 | 2012 | 62 | |
| 8 | 2017 | 42 | |
| 9 | 2011 | 23 | |
| 10 | 2021 | 16 | |
| 11 | 2021 | 16 | |
| 12 | 2019 | 14 | |
| 13 | 2017 | 12 | |
| 14 | 2024 | 8 | |
| 15 | 2023 | 6 | |
| 16 | 2024 | 1 | |
| 17 | 2023 | 1 | |
| 18 | 2002 | 1 |
About Chun-Chin Chen
Chun-Chin Chen is a scholar working on Molecular Biology, Oncology, Hematology, Genetics and Mechanical Engineering, having authored 18 papers that have together received 861 indexed citations. Recurring topics across this work include CRISPR and Genetic Engineering (7 papers), DNA Repair Mechanisms (7 papers), Acute Myeloid Leukemia Research (4 papers), PARP inhibition in cancer therapy (4 papers), Epigenetics and DNA Methylation (3 papers), Cancer Genomics and Diagnostics (2 papers), Child Nutrition and Feeding Issues (1 paper) and TGF-β signaling in diseases (1 paper). The work is most often cited by research in Oncology (278 citations), Cancer Research (136 citations), Molecular Biology (560 citations), Biomaterials (91 citations) and Aging (8 citations). Chun-Chin Chen has collaborated with scholars based in United States, Taiwan and Brazil. Frequent co-authors include Maria Jasin, Elizabeth M. Kass, Weiran Feng, Pei Xin Lim, Franklin Chau‐Nan Hong, Chih-Fu Yang, Jin‐Yuh Shew, Eva Y.-H.P. Lee, King‐Jen Chang and Mary Ellen Moynahan. Their work appears in journals such as Leukemia, Proceedings of the National Academy of Sciences, Cancer Research, Applied Surface Science and Cell 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.