Yu-Chieh Wang
- Cancer Research top 5%
- Molecular Biology top 5%
- CRISPR and Genetic Engineering 6
- Pluripotent Stem Cells Research 6
- PI3K/AKT/mTOR signaling in cancer 3
- Peroxisome Proliferator-Activated Receptors 3
- Renal and related cancers 3
- Biophysics top 5%
- Oncology top 10%
- Cancer-related Molecular Pathways 3
- Immunology top 10%
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- Pancreatic function and diabetes 4
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- Face recognition and analysis 3
- Co-authors
- Jeanne F. LoringLouise C. LaurentSuzanne E. PetersonGary P. SchrothQiaolin DengIrina KhrebtukovaShujun LuoRobin Li
- Partner nations
- United StatesTaiwanChina
In The Last Decade
Yu-Chieh Wang
45 papers receiving 2.7k citations
Hit Papers
Peers
Comparison fields: 5 of 147
- Cancer Research 589
- Molecular Biology 2.0k
- Biophysics 106
- Oncology 431
- Immunology 279
Countries citing papers authored by Yu-Chieh Wang
This map shows the geographic impact of Yu-Chieh 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 Yu-Chieh Wang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Yu-Chieh Wang more than expected).
Fields of papers citing papers by Yu-Chieh Wang
This network shows the impact of papers produced by Yu-Chieh 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 Yu-Chieh Wang. The network helps show where Yu-Chieh Wang may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Yu-Chieh 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
| # | Work | ||
|---|---|---|---|
| 1 | 2024 | 1 | |
| 2 | 2023 | 1 | |
| 3 | 2022 | 19 | |
| 4 | 2020 | 43 | |
| 5 | 2020 | 11 | |
| 6 | 2017 | 7 | |
| 7 | 2016 | 18 | |
| 8 | 2015 | 50 | |
| 9 | 2015 | 4 | |
| 10 | 2013 | 40 | |
| 11 | 2013 | 273 | |
| 12 | Full-length mRNA-Seq from single-cell levels of RNA and individual circulating tumor cellsbreakdown → | 2012 | 1174 |
| 13 | 2011 | 137 | |
| 14 | A novel multi-task support vector sample learning technique to predict classification of cancer | 2010 | 1 |
| 15 | 2008 | 51 | |
| 16 | 2008 | 52 | |
| 17 | 2007 | 82 | |
| 18 | 2007 | 66 | |
| 19 | 2003 | 36 | |
| 20 | 2002 | 14 |
About Yu-Chieh Wang
Yu-Chieh Wang is a scholar working on Cancer Research, Molecular Biology and Geriatrics and Gerontology, having authored 48 papers that have together received 2.7k indexed citations. Recurring topics across this work include CRISPR and Genetic Engineering (6 papers), Pluripotent Stem Cells Research (6 papers), Pancreatic function and diabetes (4 papers), Face recognition and analysis (3 papers), PI3K/AKT/mTOR signaling in cancer (3 papers), Peroxisome Proliferator-Activated Receptors (3 papers), Cancer-related Molecular Pathways (3 papers) and Renal and related cancers (3 papers). The work is most often cited by research in Cancer Research (589 citations), Molecular Biology (2.0k citations) and Biophysics (106 citations). Yu-Chieh Wang has collaborated with scholars based in United States, Taiwan and China. Frequent co-authors include Jeanne F. Loring, Louise C. Laurent, Suzanne E. Peterson, Gary P. Schroth, Qiaolin Deng, Irina Khrebtukova, Shujun Luo, Robin Li, Gregory A. Daniels and Daniel Ramsköld. Their work appears in journals such as Journal of Clinical Oncology, Nature Biotechnology and PLoS ONE.
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.