Yejun Wang
Impact in
- Endocrinology top 2%
- Vibrio bacteria research studies
- Molecular Biology top 5%
- RNA Research and Splicing
- RNA modifications and cancer
- Genomics and Phylogenetic Studies
- RNA and protein synthesis mechanisms
- Genomics and Chromatin Dynamics
- RNA Interference and Gene Delivery
- Machine Learning in Bioinformatics
Papers in
-
- Genomics and Phylogenetic Studies 11
- RNA modifications and cancer 8
- RNA Research and Splicing 7
- Genomics and Chromatin Dynamics 7
- RNA and protein synthesis mechanisms 7
- Genetics 13
- Bacterial Genetics and Biotechnology 6
- Co-authors
- Dianjing Guo (13 shared papers)G. V. Shivashankar (8 shared papers)Ming‐an Sun (7 shared papers)Aaron P. White (18 shared papers)Yan Qi (1 shared paper)Qing Zhang (1 shared paper)Wei Wang (1 shared paper)Hongxia Bao (3 shared papers)
In The Last Decade
Yejun Wang
109 papers receiving 2.8k citations
Peers
Comparison fields: 5 of 144
- Endocrinology 225
- Molecular Biology 1.6k
- Cancer Research 256
- Cell Biology 264
- Molecular Medicine 57
Countries citing papers authored by Yejun Wang
This map shows the geographic impact of Yejun Wang'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 Yejun Wang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Yejun Wang more than expected).
Fields of papers citing papers by Yejun Wang
This network shows the impact of papers produced by Yejun Wang. 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 Yejun Wang. The network helps show where Yejun Wang may publish in the future.
Co-authors
The 25 scholars most cited alongside Yejun Wang, 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 114 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2017 | 282 | |
| 2 | 2009 | 165 | |
| 3 | 2013 | 111 | |
| 4 | 2020 | 104 | |
| 5 | 2011 | 95 | |
| 6 | 2017 | 86 | |
| 7 | 2014 | 84 | |
| 8 | 2015 | 65 | |
| 9 | 2017 | 63 | |
| 10 | 2018 | 63 | |
| 11 | 2014 | 61 | |
| 12 | 2012 | 56 | |
| 13 | 2019 | 55 | |
| 14 | 2016 | 54 | |
| 15 | 2015 | 53 | |
| 16 | 2010 | 49 | |
| 17 | 2017 | 43 | |
| 18 | 2006 | 43 | |
| 19 | 2017 | 41 | |
| 20 | 2014 | 41 |
About Yejun Wang
Yejun Wang is a scholar working on Molecular Biology, Genetics, Ecology, Endocrinology and Cancer Research, having authored 114 papers that have together received 2.8k indexed citations. Recurring topics across this work include Genomics and Phylogenetic Studies (11 papers), Vibrio bacteria research studies (9 papers), RNA modifications and cancer (8 papers), RNA Research and Splicing (7 papers), Genomics and Chromatin Dynamics (7 papers), Salmonella and Campylobacter epidemiology (7 papers), RNA and protein synthesis mechanisms (7 papers) and Bacterial Genetics and Biotechnology (6 papers). The work is most often cited by research in Endocrinology (225 citations), Molecular Biology (1.6k citations), Cancer Research (256 citations), Cell Biology (264 citations) and Molecular Medicine (57 citations). Yejun Wang has collaborated with scholars based in China, Hong Kong and Canada. Frequent co-authors include Dianjing Guo, G. V. Shivashankar, Ming‐an Sun, Aaron P. White, Yan Qi, Qing Zhang, Wei Wang, Hongxia Bao, Yueming Hu and Caroline Uhler. Their work appears in journals such as PLoS ONE, Bioinformatics, BMC Genomics, Scientific Reports and Infection and Immunity.
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.