Hailong Wu
- Molecular Biology top 2%
- Cancer Research top 0.5%
- Oncology top 10%
- Immunology top 10%
- Pulmonary and Respiratory Medicine
- Co-authors
- Yin‐Yuan MoMin-Liang SiFangting WuShoumin ZhuShijie ShengDaotai NieYin-Yuan MoMohit Sachdeva
- Topics
- MicroRNA in disease regulation (12 papers)Cancer-related molecular mechanisms research (11 papers)RNA modifications and cancer (10 papers)
- Journals
- Proceedings of the National Academy of SciencesJournal of Biological ChemistryApplied and Environmental Microbiology
- Partner nations
- ChinaUnited StatesMexico
In The Last Decade
Hailong Wu
55 papers receiving 4.3k citations
Hit Papers
Peers
Comparison fields: 5 of 127
- Molecular Biology 3.4k
- Cancer Research 2.6k
- Oncology 452
- Immunology 263
- Pulmonary and Respiratory Medicine 188
Countries citing papers authored by Hailong Wu
This map shows the geographic impact of Hailong Wu'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 Hailong Wu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Hailong Wu more than expected).
Fields of papers citing papers by Hailong Wu
This network shows the impact of papers produced by Hailong Wu. 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 Hailong Wu. The network helps show where Hailong Wu may publish in the future.
Co-authorship network of co-authors of Hailong Wu
This figure shows the co-authorship network connecting the top 25 collaborators of Hailong Wu. A scholar is included among the top collaborators of Hailong Wu based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Hailong Wu. Hailong Wu is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 8 | |
| 3 | 5 | |
| 4 | 6 | |
| 5 | 13 | |
| 6 | 34 | |
| 7 | 46 | |
| 8 | 23 | |
| 9 | 8 | |
| 10 | 14 | |
| 11 | 11 | |
| 12 | 55 | |
| 13 | 153 | |
| 14 | 315 | |
| 15 | p53 represses c-Myc through induction of the tumor suppressor miR-145breakdown → | 691 |
| 16 | 56 | |
| 17 | MicroRNA-21 targets tumor suppressor genes in invasion and metastasisbreakdown → | 894 |
| 18 | 6 | |
| 19 | MicroRNA-21 Targets the Tumor Suppressor Gene Tropomyosin 1 (TPM1)breakdown → | 919 |
| 20 | 21 |
About Hailong Wu
Hailong Wu is a scholar working on Computational Mathematics, Cancer Research and Molecular Biology, having authored 58 papers that have together received 4.3k indexed citations. Recurring topics across this work include MicroRNA in disease regulation (12 papers), Cancer-related molecular mechanisms research (11 papers) and RNA modifications and cancer (10 papers). The work is most often cited by research in Cancer Research (2.6k citations), Molecular Biology (3.4k citations) and Oncology (452 citations). Hailong Wu has collaborated with scholars based in China, United States and Mexico. Frequent co-authors include Yin‐Yuan Mo, Min-Liang Si, Fangting Wu, Shoumin Zhu, Shijie Sheng, Daotai Nie, Yin-Yuan Mo, Mohit Sachdeva, Kounosuke Watabe and Sumit Kumar. Their work appears in journals such as Proceedings of the National Academy of Sciences, Journal of Biological Chemistry and Applied and Environmental Microbiology.
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.