Won‐Mo Yang
Impact in
- Cancer Research top 5%
- MicroRNA in disease regulation
- Cancer-related molecular mechanisms research
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- Circular RNAs in diseases
- RNA modifications and cancer
- Metabolism, Diabetes, and Cancer
Papers in
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- MicroRNA in disease regulation 13
- Cancer-related molecular mechanisms research 10
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- Circular RNAs in diseases 7
- Metabolism, Diabetes, and Cancer 2
- RNA modifications and cancer 2
- Co-authors
- Wan Lee (15 shared papers)Hyo‐Jin Jeong (5 shared papers)Seung‐Yoon Park (4 shared papers)Hyo Won Jung (1 shared paper)Woo Kyung Kim (1 shared paper)Young‐Won Chin (1 shared paper)Joo‐Hyun Nam (1 shared paper)Young‐Bum Kim (5 shared papers)
- Journals
- Data in Brief (6 papers)Biochemical and Biophysical Research Communications (4 papers)Molecular Metabolism (2 papers)FEBS Letters (2 papers)Diabetes (1 paper)
- Partner nations
- South KoreaUnited StatesJapan
In The Last Decade
Won‐Mo Yang
21 papers receiving 499 citations
Peers
Comparison fields: 5 of 71
- Cancer Research 289
- Molecular Biology 277
- Physiology 75
- Sensory Systems 9
- Geriatrics and Gerontology 6
Countries citing papers authored by Won‐Mo Yang
This map shows the geographic impact of Won‐Mo Yang'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‐Mo Yang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Won‐Mo Yang more than expected).
Fields of papers citing papers by Won‐Mo Yang
This network shows the impact of papers produced by Won‐Mo Yang. 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‐Mo Yang. The network helps show where Won‐Mo Yang may publish in the future.
Co-authors
The 25 scholars most cited alongside Won‐Mo Yang, 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 21 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2014 | 86 | |
| 2 | 2015 | 76 | |
| 3 | 2014 | 64 | |
| 4 | 2016 | 53 | |
| 5 | 2013 | 36 | |
| 6 | 2018 | 34 | |
| 7 | 2013 | 34 | |
| 8 | 2016 | 25 | |
| 9 | 2017 | 21 | |
| 10 | 2014 | 21 | |
| 11 | 2016 | 13 | |
| 12 | 2017 | 6 | |
| 13 | 2024 | 5 | |
| 14 | 2020 | 5 | |
| 15 | 2017 | 5 | |
| 16 | 2022 | 4 | |
| 17 | 2024 | 4 | |
| 18 | 2016 | 4 | |
| 19 | 2015 | 3 | |
| 20 | 2017 | 3 |
About Won‐Mo Yang
Won‐Mo Yang is a scholar working on Cancer Research, Molecular Biology, Physiology, Surgery and Endocrine and Autonomic Systems, having authored 21 papers that have together received 503 indexed citations. Recurring topics across this work include MicroRNA in disease regulation (13 papers), Cancer-related molecular mechanisms research (10 papers), Circular RNAs in diseases (7 papers), Adipose Tissue and Metabolism (5 papers), Metabolism, Diabetes, and Cancer (2 papers), Regulation of Appetite and Obesity (2 papers), Pancreatic function and diabetes (2 papers) and RNA modifications and cancer (2 papers). The work is most often cited by research in Cancer Research (289 citations), Molecular Biology (277 citations), Physiology (75 citations), Sensory Systems (9 citations) and Geriatrics and Gerontology (6 citations). Won‐Mo Yang has collaborated with scholars based in South Korea, United States and Japan. Frequent co-authors include Wan Lee, Hyo‐Jin Jeong, Seung‐Yoon Park, Hyo Won Jung, Woo Kyung Kim, Young‐Won Chin, Joo‐Hyun Nam, Young‐Bum Kim, Jae Hyeon Kim and Moon‐Kyu Lee. Their work appears in journals such as Data in Brief, Biochemical and Biophysical Research Communications, Molecular Metabolism, FEBS Letters and Diabetes.
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.