Jun‐Yang Liou
Impact in
- Pharmacology top 2%
- Inflammatory mediators and NSAID effects
- Biochemistry top 2%
- Eicosanoids and Hypertension Pharmacology
Papers in
-
- 14-3-3 protein interactions 14
- Pluripotent Stem Cells Research 7
- Ubiquitin and proteasome pathways 6
- RNA Interference and Gene Delivery 4
- Peroxisome Proliferator-Activated Receptors 4
- Pharmacology 18
- Inflammatory mediators and NSAID effects 14
- Co-authors
- Kenneth K. Wu (28 shared papers)Song‐Kun Shyue (23 shared papers)Bor‐Sheng Ko (30 shared papers)Yee‐Jee Jan (19 shared papers)Shu-Man Liang (18 shared papers)Kenneth K. Wu (1 shared paper)Shu‐Hui Juan (1 shared paper)Lee‐Young Chau (1 shared paper)
- Journals
- PLoS ONE (8 papers)Oncotarget (5 papers)Circulation (4 papers)Cancers (3 papers)Arteriosclerosis Thrombosis and Vascular Biology (3 papers)
- Partner nations
- TaiwanUnited StatesChina
In The Last Decade
Jun‐Yang Liou
67 papers receiving 2.5k citations
Peers
Comparison fields: 5 of 103
- Pharmacology 452
- Biochemistry 193
- Molecular Biology 1.5k
- Cancer Research 274
- Cell Biology 277
Countries citing papers authored by Jun‐Yang Liou
This map shows the geographic impact of Jun‐Yang Liou'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‐Yang Liou with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jun‐Yang Liou more than expected).
Fields of papers citing papers by Jun‐Yang Liou
This network shows the impact of papers produced by Jun‐Yang Liou. 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‐Yang Liou. The network helps show where Jun‐Yang Liou may publish in the future.
Co-authors
The 25 scholars most cited alongside Jun‐Yang Liou, 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 69 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2001 | 276 | |
| 2 | 2006 | 121 | |
| 3 | 2005 | 115 | |
| 4 | 2009 | 99 | |
| 5 | 2007 | 88 | |
| 6 | 2001 | 83 | |
| 7 | 2000 | 74 | |
| 8 | 2005 | 71 | |
| 9 | 2002 | 67 | |
| 10 | 2007 | 62 | |
| 11 | 2015 | 62 | |
| 12 | 2013 | 60 | |
| 13 | 2005 | 60 | |
| 14 | 2005 | 60 | |
| 15 | 2010 | 52 | |
| 16 | 2011 | 45 | |
| 17 | 2020 | 44 | |
| 18 | 2015 | 44 | |
| 19 | 2001 | 44 | |
| 20 | 2011 | 39 |
About Jun‐Yang Liou
Jun‐Yang Liou is a scholar working on Molecular Biology, Pharmacology, Cell Biology, Oncology and Immunology and Allergy, having authored 69 papers that have together received 2.5k indexed citations. Recurring topics across this work include 14-3-3 protein interactions (14 papers), Inflammatory mediators and NSAID effects (14 papers), Pluripotent Stem Cells Research (7 papers), Cell Adhesion Molecules Research (7 papers), Ubiquitin and proteasome pathways (6 papers), Caveolin-1 and cellular processes (6 papers), RNA Interference and Gene Delivery (4 papers) and Peroxisome Proliferator-Activated Receptors (4 papers). The work is most often cited by research in Pharmacology (452 citations), Biochemistry (193 citations), Molecular Biology (1.5k citations), Cancer Research (274 citations) and Cell Biology (277 citations). Jun‐Yang Liou has collaborated with scholars based in Taiwan, United States and China. Frequent co-authors include Kenneth K. Wu, Song‐Kun Shyue, Bor‐Sheng Ko, Yee‐Jee Jan, Shu-Man Liang, Kenneth K. Wu, Shu‐Hui Juan, Lee‐Young Chau, Tzong‐Shyuan Lee and Kuang‐Wen Tseng. Their work appears in journals such as PLoS ONE, Oncotarget, Circulation, Cancers and Arteriosclerosis Thrombosis and Vascular Biology.
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.