Deying Yang
Impact in
- Aging top 2%
- Genetics, Aging, and Longevity in Model Organisms
- Cancer Research top 10%
- Cancer-related molecular mechanisms research
- MicroRNA in disease regulation
Papers in
-
- Gut microbiota and health 5
- Circular RNAs in diseases 5
- Aging 12
- Genetics, Aging, and Longevity in Model Organisms 12
- Co-authors
- Mingyao Yang (36 shared papers)Xiaolan Fan (36 shared papers)Xueping Mao (12 shared papers)Mingwang Zhang (21 shared papers)Diyan Li (15 shared papers)Uma Gaur (11 shared papers)Zhi He (24 shared papers)Bo Zeng (10 shared papers)
- Journals
- International Journal of Molecular Sciences (7 papers)Animals (4 papers)BMC Genomics (4 papers)Mechanisms of Ageing and Development (4 papers)Experimental Gerontology (3 papers)
- Partner nations
- ChinaUnited StatesAustralia
In The Last Decade
Deying Yang
63 papers receiving 1.2k citations
Peers
Comparison fields: 5 of 110
- Aging 133
- Cancer Research 168
- Biological Psychiatry 19
- Molecular Biology 509
- Biochemistry 42
Countries citing papers authored by Deying Yang
This map shows the geographic impact of Deying 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 Deying Yang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Deying Yang more than expected).
Fields of papers citing papers by Deying Yang
This network shows the impact of papers produced by Deying 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 Deying Yang. The network helps show where Deying Yang may publish in the future.
Co-authors
The 25 scholars most cited alongside Deying 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 66 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2020 | 94 | |
| 2 | 2022 | 93 | |
| 3 | 2021 | 93 | |
| 4 | 2020 | 69 | |
| 5 | 2022 | 68 | |
| 6 | 2015 | 66 | |
| 7 | 2016 | 62 | |
| 8 | 2020 | 57 | |
| 9 | 2012 | 36 | |
| 10 | 2017 | 34 | |
| 11 | 2016 | 34 | |
| 12 | 2020 | 31 | |
| 13 | 2021 | 27 | |
| 14 | 2017 | 24 | |
| 15 | 2017 | 22 | |
| 16 | 2016 | 21 | |
| 17 | 2021 | 20 | |
| 18 | 2023 | 18 | |
| 19 | 2020 | 18 | |
| 20 | 2020 | 17 |
About Deying Yang
Deying Yang is a scholar working on Molecular Biology, Aging, Physiology, Genetics and Cancer Research, having authored 66 papers that have together received 1.2k indexed citations. Recurring topics across this work include Genetics, Aging, and Longevity in Model Organisms (12 papers), Cancer-related molecular mechanisms research (8 papers), Reproductive biology and impacts on aquatic species (8 papers), Gut microbiota and health (5 papers), Invertebrate Immune Response Mechanisms (5 papers), Genetic and Clinical Aspects of Sex Determination and Chromosomal Abnormalities (5 papers), Circular RNAs in diseases (5 papers) and Aquaculture Nutrition and Growth (4 papers). The work is most often cited by research in Aging (133 citations), Cancer Research (168 citations), Biological Psychiatry (19 citations), Molecular Biology (509 citations) and Biochemistry (42 citations). Deying Yang has collaborated with scholars based in China, United States and Australia. Frequent co-authors include Mingyao Yang, Xiaolan Fan, Xueping Mao, Mingwang Zhang, Diyan Li, Uma Gaur, Zhi He, Bo Zeng, Ting Lian and Yue Gao. Their work appears in journals such as International Journal of Molecular Sciences, Animals, BMC Genomics, Mechanisms of Ageing and Development and Experimental Gerontology.
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.