Chang-ye Chen
Impact in
- Reproductive Medicine top 10%
- Ovarian function and disorders
- Ovarian cancer diagnosis and treatment
Papers in
-
- Epigenetics and DNA Methylation 2
- FOXO transcription factor regulation 1
-
- Cancer-related molecular mechanisms research 2
- MicroRNA in disease regulation 1
- Co-authors
- Yukun Li (3 shared papers)Guifang Luo (3 shared papers)Yan Li (1 shared paper)Jiao Xiao (1 shared paper)Yan Ma (1 shared paper)Daichao Wu (1 shared paper)Juan Wang (2 shared papers)Tian Zeng (1 shared paper)
- Journals
- Life Sciences (2 papers)Medicine (2 papers)Bioscience Reports (1 paper)Cancer Cell International (1 paper)Experimental Cell Research (1 paper)
- Partner nations
- ChinaUnited States
In The Last Decade
Chang-ye Chen
11 papers receiving 248 citations
Peers
Comparison fields: 5 of 69
- Reproductive Medicine 97
- Health Informatics 11
- Cancer Research 47
- Public Health, Environmental and Occupational Health 62
- Endocrinology, Diabetes and Metabolism 25
Countries citing papers authored by Chang-ye Chen
This map shows the geographic impact of Chang-ye 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 Chang-ye Chen with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Chang-ye Chen more than expected).
Fields of papers citing papers by Chang-ye Chen
This network shows the impact of papers produced by Chang-ye 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 Chang-ye Chen. The network helps show where Chang-ye Chen may publish in the future.
Co-authors
The 25 scholars most cited alongside Chang-ye 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 | 2019 | 125 | |
| 2 | 2022 | 38 | |
| 3 | 2020 | 21 | |
| 4 | 2024 | 18 | |
| 5 | 2019 | 16 | |
| 6 | 2018 | 10 | |
| 7 | 2020 | 9 | |
| 8 | 2019 | 8 | |
| 9 | 2021 | 8 | |
| 10 | 2023 | 2 | |
| 11 | 2018 | 1 |
About Chang-ye Chen
Chang-ye Chen is a scholar working on Molecular Biology, Cancer Research, Health Informatics, Public Health, Environmental and Occupational Health and Safety Research, having authored 11 papers that have together received 256 indexed citations. Recurring topics across this work include Artificial Intelligence in Healthcare and Education (2 papers), Epigenetics and DNA Methylation (2 papers), Cancer-related molecular mechanisms research (2 papers), Ovarian function and disorders (1 paper), MicroRNA in disease regulation (1 paper), Fire Detection and Safety Systems (1 paper), FOXO transcription factor regulation (1 paper) and Inflammation biomarkers and pathways (1 paper). The work is most often cited by research in Reproductive Medicine (97 citations), Health Informatics (11 citations), Cancer Research (47 citations), Public Health, Environmental and Occupational Health (62 citations) and Endocrinology, Diabetes and Metabolism (25 citations). Chang-ye Chen has collaborated with scholars based in China and United States. Frequent co-authors include Yukun Li, Guifang Luo, Yan Li, Jiao Xiao, Yan Ma, Daichao Wu, Yukun Li, Juan Wang, Tian Zeng and Guan Yang. Their work appears in journals such as Life Sciences, Medicine, Bioscience Reports, Cancer Cell International and Experimental Cell Research.
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.