Cuixia Di
Impact in
- Cancer Research top 5%
- MicroRNA in disease regulation
- Cancer-related molecular mechanisms research
- Molecular Biology top 10%
- RNA modifications and cancer
- Mitochondrial Function and Pathology
- RNA Research and Splicing
- Circular RNAs in diseases
Papers in
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- RNA Research and Splicing 12
- RNA modifications and cancer 11
- Mitochondrial Function and Pathology 7
- Cell death mechanisms and regulation 7
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- Cancer-related molecular mechanisms research 8
- MicroRNA in disease regulation 7
- Co-authors
- Jing Si (29 shared papers)Chao Sun (18 shared papers)Hong Zhang (16 shared papers)Qiang Li (8 shared papers)Yupei Wang (10 shared papers)Xiaodong Jin (7 shared papers)Lu Gan (15 shared papers)Xiaodong Xie (8 shared papers)
In The Last Decade
Cuixia Di
74 papers receiving 2.1k citations
Cuixia Di's Hit Papers
Peers
Comparison fields: 5 of 120
- Cancer Research 414
- Molecular Biology 1.2k
- Biochemistry 84
- Oncology 268
- Pulmonary and Respiratory Medicine 250
Countries citing papers authored by Cuixia Di
This map shows the geographic impact of Cuixia Di'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 Cuixia Di with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Cuixia Di more than expected).
Fields of papers citing papers by Cuixia Di
This network shows the impact of papers produced by Cuixia Di. 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 Cuixia Di. The network helps show where Cuixia Di may publish in the future.
Co-authors
The 25 scholars most cited alongside Cuixia Di, 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 74 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | Mutant p53 in cancer: from molecular mechanism to therapeutic modulation Hit paper breakdown → | 2022 | 286 |
| 2 | 2019 | 162 | |
| 3 | 2009 | 108 | |
| 4 | 2023 | 84 | |
| 5 | 2019 | 77 | |
| 6 | 2018 | 70 | |
| 7 | 2016 | 70 | |
| 8 | 2017 | 69 | |
| 9 | 2018 | 68 | |
| 10 | 2018 | 61 | |
| 11 | 2023 | 59 | |
| 12 | 2018 | 56 | |
| 13 | 2015 | 53 | |
| 14 | 2021 | 51 | |
| 15 | 2006 | 43 | |
| 16 | 2022 | 39 | |
| 17 | 2019 | 35 | |
| 18 | 2021 | 34 | |
| 19 | 2014 | 33 | |
| 20 | 2020 | 33 |
About Cuixia Di
Cuixia Di is a scholar working on Molecular Biology, Cancer Research, Oncology, Pulmonary and Respiratory Medicine and Biochemistry, having authored 74 papers that have together received 2.2k indexed citations. Recurring topics across this work include RNA Research and Splicing (12 papers), RNA modifications and cancer (11 papers), Cancer-related Molecular Pathways (9 papers), Radiation Therapy and Dosimetry (8 papers), Cancer-related molecular mechanisms research (8 papers), Mitochondrial Function and Pathology (7 papers), Cell death mechanisms and regulation (7 papers) and MicroRNA in disease regulation (7 papers). The work is most often cited by research in Cancer Research (414 citations), Molecular Biology (1.2k citations), Biochemistry (84 citations), Oncology (268 citations) and Pulmonary and Respiratory Medicine (250 citations). Cuixia Di has collaborated with scholars based in China, Japan and Germany. Frequent co-authors include Jing Si, Chao Sun, Hong Zhang, Qiang Li, Yupei Wang, Xiaodong Jin, Lu Gan, Xiaodong Xie, Zhihui Dou and Aihong Mao. Their work appears in journals such as Journal of Cellular Physiology, Oncology Reports, Artificial Cells Nanomedicine and Biotechnology, Cell Death and Disease and Scientific 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.