Won‐Jing Wang
Impact in
- Cell Biology top 1%
- Microtubule and mitosis dynamics
- Genetics top 2%
- Genetic and Kidney Cyst Diseases
Papers in
-
- Protist diversity and phylogeny 9
- Hedgehog Signaling Pathway Studies 4
- Ubiquitin and proteasome pathways 4
- Epigenetics and DNA Methylation 3
- Cell Biology 20
- Microtubule and mitosis dynamics 15
- Cellular Mechanics and Interactions 3
- Co-authors
- Meng-Fu Bryan Tsou (10 shared papers)Kunihiro Uryu (5 shared papers)Ruey‐Hwa Chen (8 shared papers)Jean‐Cheng Kuo (6 shared papers)Rajesh K. Soni (3 shared papers)B Tanos (4 shared papers)Chung‐Chen Jane Yao (2 shared papers)John M. Asara (2 shared papers)
- Journals
- The Journal of Cell Biology (4 papers)Nature Communications (3 papers)Developmental Cell (3 papers)Cell Reports (2 papers)EMBO Reports (2 papers)
- Partner nations
- TaiwanUnited StatesUnited Kingdom
In The Last Decade
Won‐Jing Wang
36 papers receiving 2.4k citations
Peers
Comparison fields: 5 of 109
- Cell Biology 1.2k
- Genetics 898
- Molecular Biology 1.9k
- Structural Biology 29
- Aging 26
Countries citing papers authored by Won‐Jing Wang
This map shows the geographic impact of Won‐Jing 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 Won‐Jing Wang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Won‐Jing Wang more than expected).
Fields of papers citing papers by Won‐Jing Wang
This network shows the impact of papers produced by Won‐Jing 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 Won‐Jing Wang. The network helps show where Won‐Jing Wang may publish in the future.
Co-authors
The 25 scholars most cited alongside Won‐Jing 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 38 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2013 | 306 | |
| 2 | 2009 | 233 | |
| 3 | 2004 | 193 | |
| 4 | 2018 | 182 | |
| 5 | 2018 | 144 | |
| 6 | 2002 | 134 | |
| 7 | 2011 | 126 | |
| 8 | 2015 | 114 | |
| 9 | 2016 | 104 | |
| 10 | 2006 | 97 | |
| 11 | 2014 | 84 | |
| 12 | 2019 | 75 | |
| 13 | 2013 | 73 | |
| 14 | 2007 | 65 | |
| 15 | 2020 | 58 | |
| 16 | 2019 | 50 | |
| 17 | 2019 | 49 | |
| 18 | 2015 | 48 | |
| 19 | 2002 | 47 | |
| 20 | 2017 | 37 |
About Won‐Jing Wang
Won‐Jing Wang is a scholar working on Molecular Biology, Cell Biology, Genetics, Epidemiology and Immunology, having authored 38 papers that have together received 2.5k indexed citations. Recurring topics across this work include Genetic and Kidney Cyst Diseases (18 papers), Microtubule and mitosis dynamics (15 papers), Protist diversity and phylogeny (9 papers), Hedgehog Signaling Pathway Studies (4 papers), Ubiquitin and proteasome pathways (4 papers), Epigenetics and DNA Methylation (3 papers), Chromosomal and Genetic Variations (3 papers) and Cellular Mechanics and Interactions (3 papers). The work is most often cited by research in Cell Biology (1.2k citations), Genetics (898 citations), Molecular Biology (1.9k citations), Structural Biology (29 citations) and Aging (26 citations). Won‐Jing Wang has collaborated with scholars based in Taiwan, United States and United Kingdom. Frequent co-authors include Meng-Fu Bryan Tsou, Kunihiro Uryu, Ruey‐Hwa Chen, Jean‐Cheng Kuo, Rajesh K. Soni, B Tanos, Chung‐Chen Jane Yao, John M. Asara, Frank Macaluso and Jung‐Chi Liao. Their work appears in journals such as The Journal of Cell Biology, Nature Communications, Developmental Cell, Cell Reports and EMBO Reports.
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.