Jun Yin
Impact in
- Cancer Research top 5%
- MicroRNA in disease regulation
- Cancer-related molecular mechanisms research
- Molecular Biology top 5%
- Genomics and Chromatin Dynamics
- RNA Research and Splicing
- RNA modifications and cancer
- Epigenetics and DNA Methylation
- Circular RNAs in diseases
Papers in
-
- RNA modifications and cancer 10
- Epigenetics and DNA Methylation 8
- Circular RNAs in diseases 5
- Genomics and Chromatin Dynamics 5
- RNA Research and Splicing 4
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- MicroRNA in disease regulation 11
- Cancer-related molecular mechanisms research 9
- Co-authors
- James P. Noonan (6 shared papers)Steven K. Reilly (5 shared papers)Justin Cotney (4 shared papers)Deena Emera (3 shared papers)Jing Leng (3 shared papers)Albert E. Ayoub (2 shared papers)Pasko Rakić (2 shared papers)Jian Zhao (11 shared papers)
- Journals
- PLoS ONE (6 papers)Genome Research (3 papers)Scientific Reports (3 papers)BMC Genomics (2 papers)Medicine (2 papers)
- Partner nations
- ChinaUnited StatesIreland
In The Last Decade
Jun Yin
74 papers receiving 2.0k citations
Peers
Comparison fields: 5 of 129
- Cancer Research 365
- Molecular Biology 1.2k
- Genetics 385
- Developmental Neuroscience 47
- Geriatrics and Gerontology 29
Countries citing papers authored by Jun Yin
This map shows the geographic impact of Jun Yin'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 Yin with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jun Yin more than expected).
Fields of papers citing papers by Jun Yin
This network shows the impact of papers produced by Jun Yin. 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 Yin. The network helps show where Jun Yin may publish in the future.
Co-authors
The 25 scholars most cited alongside Jun Yin, 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 79 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2015 | 215 | |
| 2 | 2015 | 189 | |
| 3 | 2012 | 148 | |
| 4 | 2013 | 147 | |
| 5 | 2011 | 93 | |
| 6 | 2013 | 85 | |
| 7 | 2014 | 79 | |
| 8 | 2018 | 77 | |
| 9 | 2016 | 66 | |
| 10 | 2014 | 61 | |
| 11 | 2015 | 57 | |
| 12 | 2017 | 50 | |
| 13 | 2017 | 47 | |
| 14 | 2015 | 35 | |
| 15 | 2020 | 33 | |
| 16 | 2017 | 33 | |
| 17 | 2017 | 30 | |
| 18 | 2017 | 30 | |
| 19 | 2018 | 29 | |
| 20 | 2014 | 29 |
About Jun Yin
Jun Yin is a scholar working on Molecular Biology, Cancer Research, Genetics, Epidemiology and Plant Science, having authored 79 papers that have together received 2.0k indexed citations. Recurring topics across this work include MicroRNA in disease regulation (11 papers), RNA modifications and cancer (10 papers), Cancer-related molecular mechanisms research (9 papers), Epigenetics and DNA Methylation (8 papers), Genetics and Neurodevelopmental Disorders (6 papers), Circular RNAs in diseases (5 papers), Genomics and Chromatin Dynamics (5 papers) and RNA Research and Splicing (4 papers). The work is most often cited by research in Cancer Research (365 citations), Molecular Biology (1.2k citations), Genetics (385 citations), Developmental Neuroscience (47 citations) and Geriatrics and Gerontology (29 citations). Jun Yin has collaborated with scholars based in China, United States and Ireland. Frequent co-authors include James P. Noonan, Steven K. Reilly, Justin Cotney, Deena Emera, Jing Leng, Albert E. Ayoub, Pasko Rakić, Jian Zhao, Wenfan Fu and Lu Dai. Their work appears in journals such as PLoS ONE, Genome Research, Scientific Reports, BMC Genomics and Medicine.
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.