Pei-Chun Shen
- Cancer Research top 10%
- MicroRNA in disease regulation 2
- Cancer-related molecular mechanisms research 2
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- Bioinformatics and Genomic Networks 4
- Metabolomics and Mass Spectrometry Studies 3
- Gene expression and cancer classification 2
- Genomics, phytochemicals, and oxidative stress 1
- Aquatic Science top 10%
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- Bioactive Compounds and Antitumor Agents 1
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- Mesenchymal stem cell research 1
- Co-authors
- Hsin-Ling HsuYen‐An ChenHong‐Yu TsengLi‐Mei ChenYueh‐Shan WengAushia Tanzih Al HaqYi‐Chung TungKai‐Yuan Lin
- Cited by
- Cancer ResearchImmunologyOncology
- Journals
- Nucleic Acids Research (4 papers)Scientific Reports (3 papers)International Journal of Molecular Sciences (1 paper)
- Partner nations
- TaiwanUnited StatesJapan
In The Last Decade
Pei-Chun Shen
19 papers receiving 882 citations
Hit Papers
Peers
Comparison fields: 5 of 102
- Cancer Research 277
- Immunology 170
- Oncology 214
- Molecular Biology 536
- Aquatic Science 37
Countries citing papers authored by Pei-Chun Shen
This map shows the geographic impact of Pei-Chun Shen'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 Pei-Chun Shen with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Pei-Chun Shen more than expected).
Fields of papers citing papers by Pei-Chun Shen
This network shows the impact of papers produced by Pei-Chun Shen. 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 Pei-Chun Shen. The network helps show where Pei-Chun Shen may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Pei-Chun Shen, 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 | 0 | |
| 2 | 2024 | 2 | |
| 3 | 2024 | 7 | |
| 4 | 2024 | 6 | |
| 5 | 2023 | 18 | |
| 6 | 2022 | 5 | |
| 7 | 2021 | 18 | |
| 8 | 2021 | 17 | |
| 9 | 2021 | 45 | |
| 10 | 2021 | 6 | |
| 11 | 2020 | 15 | |
| 12 | 2019 | 107 | |
| 13 | MCT-1/miR-34a/IL-6/IL-6R signaling axis promotes EMT progression, cancer stemness and M2 macrophage polarization in triple-negative breast cancerbreakdown → | 2019 | 333 |
| 14 | 2019 | 138 | |
| 15 | 2017 | 42 | |
| 16 | 2015 | 30 | |
| 17 | 2013 | 34 | |
| 18 | 2013 | 27 | |
| 19 | 2013 | 42 | |
| 20 | Using an Ordered Probit Regression Model to Assess the Performance of Real Estate Brokers | 2010 | 3 |
About Pei-Chun Shen
Pei-Chun Shen is a scholar working on Cancer Research, Toxicology and Molecular Biology, having authored 20 papers that have together received 895 indexed citations. Recurring topics across this work include Bioinformatics and Genomic Networks (4 papers), Metabolomics and Mass Spectrometry Studies (3 papers), MicroRNA in disease regulation (2 papers), Cancer-related molecular mechanisms research (2 papers), Gene expression and cancer classification (2 papers), Bioactive Compounds and Antitumor Agents (1 paper), Genomics, phytochemicals, and oxidative stress (1 paper) and Mesenchymal stem cell research (1 paper). The work is most often cited by research in Cancer Research (277 citations), Immunology (170 citations) and Oncology (214 citations). Pei-Chun Shen has collaborated with scholars based in Taiwan, United States and Japan. Frequent co-authors include Hsin-Ling Hsu, Yen‐An Chen, Hong‐Yu Tseng, Li‐Mei Chen, Yueh‐Shan Weng, Aushia Tanzih Al Haq, Yi‐Chung Tung, Kai‐Yuan Lin, Wei‐Chung Cheng and George T.Y. Chen. Their work appears in journals such as Nucleic Acids Research, Scientific Reports and International Journal of Molecular Sciences.
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.