Jun Yao
Impact in
- Cancer Research top 2%
- MicroRNA in disease regulation
- Cancer-related molecular mechanisms research
- Molecular Biology top 5%
- RNA modifications and cancer
- RNA and protein synthesis mechanisms
- RNA Research and Splicing
- Extracellular vesicles in disease
Papers in
-
- RNA and protein synthesis mechanisms 15
- RNA Research and Splicing 11
- RNA modifications and cancer 10
- Bone Metabolism and Diseases 6
- CRISPR and Genetic Engineering 6
- Genetics 18
- Co-authors
- Alan M. Lambowitz (23 shared papers)Yidan Qin (6 shared papers)Ryan M. Nottingham (7 shared papers)Morayma M. Temoche-Diaz (2 shared papers)Randy Schekman (2 shared papers)Matthew J. Shurtleff (2 shared papers)Douglas C. Wu (6 shared papers)Shikai Liu (14 shared papers)
- Journals
- Fish & Shellfish Immunology (4 papers)RNA (4 papers)Scientific Reports (3 papers)eLife (3 papers)PLoS Genetics (3 papers)
- Partner nations
- ChinaUnited StatesAustralia
In The Last Decade
Jun Yao
90 papers receiving 2.9k citations
Peers
Comparison fields: 5 of 133
- Cancer Research 619
- Molecular Biology 1.7k
- Aquatic Science 173
- Rheumatology 264
- Immunology 337
Countries citing papers authored by Jun Yao
This map shows the geographic impact of Jun Yao'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 Jun Yao with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jun Yao more than expected).
Fields of papers citing papers by Jun Yao
This network shows the impact of papers produced by Jun Yao. 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 Jun Yao. The network helps show where Jun Yao may publish in the future.
Co-authors
The 25 scholars most cited alongside Jun Yao, 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 92 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2008 | 309 | |
| 2 | 2017 | 263 | |
| 3 | 2016 | 197 | |
| 4 | 2019 | 179 | |
| 5 | 2019 | 99 | |
| 6 | 2015 | 92 | |
| 7 | 2015 | 87 | |
| 8 | 2006 | 83 | |
| 9 | 2016 | 79 | |
| 10 | 2013 | 70 | |
| 11 | 2013 | 69 | |
| 12 | 2014 | 68 | |
| 13 | 2016 | 67 | |
| 14 | 2016 | 60 | |
| 15 | 2019 | 54 | |
| 16 | 2015 | 52 | |
| 17 | 2007 | 49 | |
| 18 | 2018 | 46 | |
| 19 | 2016 | 46 | |
| 20 | 2016 | 45 |
About Jun Yao
Jun Yao is a scholar working on Molecular Biology, Genetics, Cancer Research, Ecology and Immunology, having authored 92 papers that have together received 2.9k indexed citations. Recurring topics across this work include RNA and protein synthesis mechanisms (15 papers), RNA Research and Splicing (11 papers), RNA modifications and cancer (10 papers), Cancer-related molecular mechanisms research (8 papers), Aquaculture disease management and microbiota (7 papers), Bone Metabolism and Diseases (6 papers), Bacteriophages and microbial interactions (6 papers) and CRISPR and Genetic Engineering (6 papers). The work is most often cited by research in Cancer Research (619 citations), Molecular Biology (1.7k citations), Aquatic Science (173 citations), Rheumatology (264 citations) and Immunology (337 citations). Jun Yao has collaborated with scholars based in China, United States and Australia. Frequent co-authors include Alan M. Lambowitz, Yidan Qin, Ryan M. Nottingham, Morayma M. Temoche-Diaz, Randy Schekman, Matthew J. Shurtleff, Douglas C. Wu, Shikai Liu, Zhanjiang Liu and Qiang Yang. Their work appears in journals such as Fish & Shellfish Immunology, RNA, Scientific Reports, eLife and PLoS Genetics.
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.