Hai‐Yu Mo
Impact in
- Cancer Research top 5%
- Cancer Genomics and Diagnostics
- Cancer-related molecular mechanisms research
- MicroRNA in disease regulation
-
- RNA modifications and cancer
- Epigenetics and DNA Methylation
- Circular RNAs in diseases
Papers in
-
- Cancer-related molecular mechanisms research 4
- NF-κB Signaling Pathways 2
- MicroRNA in disease regulation 2
-
- RNA modifications and cancer 3
- Circular RNAs in diseases 3
- RNA Research and Splicing 2
- Co-authors
- Huai‐Qiang Ju (10 shared papers)Rui‐Hua Xu (9 shared papers)Kun Lun Liao (5 shared papers)Qi‐Nian Wu (5 shared papers)Ting Li (3 shared papers)Xiaojun Zheng (2 shared papers)Yan‐Xing Chen (3 shared papers)Hui Sheng (5 shared papers)
- Journals
- Nature Communications (2 papers)EMBO Molecular Medicine (2 papers)Cell Research (1 paper)Science Translational Medicine (1 paper)Cancer Research (1 paper)
- Partner nations
- ChinaHong KongUnited States
In The Last Decade
Hai‐Yu Mo
15 papers receiving 936 citations
Hai‐Yu Mo's Hit Papers
Peers
Comparison fields: 5 of 83
- Cancer Research 404
- Molecular Biology 497
- Oncology 174
- Health Informatics 7
- Pathology and Forensic Medicine 77
Countries citing papers authored by Hai‐Yu Mo
This map shows the geographic impact of Hai‐Yu Mo'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 Hai‐Yu Mo with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Hai‐Yu Mo more than expected).
Fields of papers citing papers by Hai‐Yu Mo
This network shows the impact of papers produced by Hai‐Yu Mo. 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 Hai‐Yu Mo. The network helps show where Hai‐Yu Mo may publish in the future.
Co-authors
The 25 scholars most cited alongside Hai‐Yu Mo, 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 | Circulating tumor DNA methylation profiles enable early diagnosis, prognosis prediction, and screening for colorectal cancer Hit paper breakdown → | 2020 | 345 |
| 2 | 2022 | 158 | |
| 3 | 2019 | 105 | |
| 4 | 2023 | 94 | |
| 5 | 2015 | 60 | |
| 6 | 2023 | 52 | |
| 7 | 2022 | 43 | |
| 8 | 2021 | 30 | |
| 9 | 2024 | 17 | |
| 10 | 2023 | 12 | |
| 11 | 2024 | 11 | |
| 12 | 2024 | 9 | |
| 13 | 2025 | 5 | |
| 14 | 2021 | 1 | |
| 15 | 2026 | 1 |
About Hai‐Yu Mo
Hai‐Yu Mo is a scholar working on Cancer Research, Molecular Biology, Immunology, Oncology and Pulmonary and Respiratory Medicine, having authored 15 papers that have together received 943 indexed citations. Recurring topics across this work include Cancer-related molecular mechanisms research (4 papers), RNA modifications and cancer (3 papers), Circular RNAs in diseases (3 papers), Immune cells in cancer (3 papers), NF-κB Signaling Pathways (2 papers), Ferroptosis and cancer prognosis (2 papers), RNA Research and Splicing (2 papers) and MicroRNA in disease regulation (2 papers). The work is most often cited by research in Cancer Research (404 citations), Molecular Biology (497 citations), Oncology (174 citations), Health Informatics (7 citations) and Pathology and Forensic Medicine (77 citations). Hai‐Yu Mo has collaborated with scholars based in China, Hong Kong and United States. Frequent co-authors include Huai‐Qiang Ju, Rui‐Hua Xu, Kun Lun Liao, Qi‐Nian Wu, Ting Li, Xiaojun Zheng, Yan‐Xing Chen, Hui Sheng, Zhao-Lei Zeng and Hai-long Piao. Their work appears in journals such as Nature Communications, EMBO Molecular Medicine, Cell Research, Science Translational Medicine and Cancer 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.