Hsueh‐Fen Juan
- Cancer Research top 1%
- Cancer, Hypoxia, and Metabolism 19
- Molecular Biology top 2%
- Bioinformatics and Genomic Networks 23
- RNA modifications and cancer 22
- RNA Research and Splicing 18
- ATP Synthase and ATPases Research 14
- Ubiquitin and proteasome pathways 12
- Immunology top 5%
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- Computational Drug Discovery Methods 13
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- Neuroblastoma Research and Treatments 20
- Co-authors
- Hsuan‐Cheng HuangChia‐Lang HsuShui‐Tein ChenLi‐Ling LinHsin‐Yi ChangChantal Hoi Yin CheungShui-Tein ChenChen-Ching Lin
- Journals
- Proceedings of the National Academy of Sciences (2 papers)Nucleic Acids Research (5 papers)Applied Physics Letters (1 paper)
- Partner nations
- TaiwanUnited StatesJapan
In The Last Decade
Hsueh‐Fen Juan
162 papers receiving 4.7k citations
Peers
Comparison fields: 5 of 149
- Cancer Research 1.1k
- Molecular Biology 3.2k
- Immunology 578
- Complementary and alternative medicine 191
- Computational Theory and Mathematics 318
Countries citing papers authored by Hsueh‐Fen Juan
This map shows the geographic impact of Hsueh‐Fen Juan'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 Hsueh‐Fen Juan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Hsueh‐Fen Juan more than expected).
Fields of papers citing papers by Hsueh‐Fen Juan
This network shows the impact of papers produced by Hsueh‐Fen Juan. 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 Hsueh‐Fen Juan. The network helps show where Hsueh‐Fen Juan may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Hsueh‐Fen Juan, 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 | 2025 | 1 | |
| 2 | 2024 | 1 | |
| 3 | 2023 | 10 | |
| 4 | 2023 | 4 | |
| 5 | 2023 | 11 | |
| 6 | 2021 | 5 | |
| 7 | 2021 | 5 | |
| 8 | 2020 | 64 | |
| 9 | 2019 | 15 | |
| 10 | 2019 | 30 | |
| 11 | 2015 | 65 | |
| 12 | 2014 | 7 | |
| 13 | 2012 | 64 | |
| 14 | 2011 | 115 | |
| 15 | 2010 | 41 | |
| 16 | 2009 | 95 | |
| 17 | 2008 | 25 | |
| 18 | 2008 | 30 | |
| 19 | 2007 | 11 | |
| 20 | 1999 | 9 |
About Hsueh‐Fen Juan
Hsueh‐Fen Juan is a scholar working on Cancer Research, Molecular Biology and Aging, having authored 165 papers that have together received 4.8k indexed citations. Recurring topics across this work include Bioinformatics and Genomic Networks (23 papers), RNA modifications and cancer (22 papers), Neuroblastoma Research and Treatments (20 papers), Cancer, Hypoxia, and Metabolism (19 papers), RNA Research and Splicing (18 papers), ATP Synthase and ATPases Research (14 papers), Computational Drug Discovery Methods (13 papers) and Ubiquitin and proteasome pathways (12 papers). The work is most often cited by research in Cancer Research (1.1k citations), Molecular Biology (3.2k citations) and Immunology (578 citations). Hsueh‐Fen Juan has collaborated with scholars based in Taiwan, United States and Japan. Frequent co-authors include Hsuan‐Cheng Huang, Chia‐Lang Hsu, Shui‐Tein Chen, Li‐Ling Lin, Hsin‐Yi Chang, Chantal Hoi Yin Cheung, Shui-Tein Chen, Chen-Ching Lin, Tsui‐Chin Huang and Wen‐Hung Kuo. Their work appears in journals such as Proceedings of the National Academy of Sciences, Nucleic Acids Research and Applied Physics Letters.
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.