Su Yang
Impact in
- Aging top 5%
-
- Genetic Neurodegenerative Diseases
Papers in
-
- Mitochondrial Function and Pathology 15
- Glycosylation and Glycoproteins Research 6
- CRISPR and Genetic Engineering 5
- Ubiquitin and proteasome pathways 4
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- Genetic Neurodegenerative Diseases 18
- Co-authors
- Xiao‐Jiang Li (21 shared papers)Shihua Li (21 shared papers)Shanshan Huang (6 shared papers)Huiming Yang (5 shared papers)Bin Liu (12 shared papers)Scott Bidlingmaier (11 shared papers)Beisha Tang (5 shared papers)Jifeng Guo (4 shared papers)
- Journals
- Blood (5 papers)Proceedings of the National Academy of Sciences (5 papers)Nature Communications (3 papers)Scientific Reports (3 papers)Molecular & Cellular Proteomics (2 papers)
- Partner nations
- ChinaUnited StatesUnited Kingdom
In The Last Decade
Su Yang
89 papers receiving 2.4k citations
Peers
Comparison fields: 5 of 101
- Aging 76
- Cellular and Molecular Neuroscience 508
- Business and International Management 48
- Oncology 520
- Molecular Biology 1.4k
Countries citing papers authored by Su Yang
This map shows the geographic impact of Su 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 Su Yang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Su Yang more than expected).
Fields of papers citing papers by Su Yang
This network shows the impact of papers produced by Su 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 Su Yang. The network helps show where Su Yang may publish in the future.
Co-authors
The 25 scholars most cited alongside Su 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 93 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2017 | 281 | |
| 2 | 2021 | 182 | |
| 3 | 2014 | 115 | |
| 4 | 2017 | 111 | |
| 5 | 2017 | 94 | |
| 6 | 2019 | 90 | |
| 7 | 2014 | 89 | |
| 8 | 2016 | 83 | |
| 9 | 2020 | 74 | |
| 10 | 2018 | 59 | |
| 11 | 2020 | 57 | |
| 12 | 2011 | 56 | |
| 13 | 2021 | 55 | |
| 14 | 2014 | 52 | |
| 15 | 2017 | 52 | |
| 16 | 2019 | 48 | |
| 17 | 2018 | 41 | |
| 18 | 2020 | 40 | |
| 19 | 2000 | 38 | |
| 20 | 2011 | 37 |
About Su Yang
Su Yang is a scholar working on Molecular Biology, Cellular and Molecular Neuroscience, Oncology, Radiology, Nuclear Medicine and Imaging and Pulmonary and Respiratory Medicine, having authored 93 papers that have together received 2.5k indexed citations. Recurring topics across this work include Genetic Neurodegenerative Diseases (18 papers), Mitochondrial Function and Pathology (15 papers), CAR-T cell therapy research (14 papers), Monoclonal and Polyclonal Antibodies Research (12 papers), Glycosylation and Glycoproteins Research (6 papers), Hepatocellular Carcinoma Treatment and Prognosis (5 papers), CRISPR and Genetic Engineering (5 papers) and Ubiquitin and proteasome pathways (4 papers). The work is most often cited by research in Aging (76 citations), Cellular and Molecular Neuroscience (508 citations), Business and International Management (48 citations), Oncology (520 citations) and Molecular Biology (1.4k citations). Su Yang has collaborated with scholars based in China, United States and United Kingdom. Frequent co-authors include Xiao‐Jiang Li, Shihua Li, Shanshan Huang, Huiming Yang, Bin Liu, Scott Bidlingmaier, Beisha Tang, Jifeng Guo, Shihua Li and Zhaohui Qin. Their work appears in journals such as Blood, Proceedings of the National Academy of Sciences, Nature Communications, Scientific Reports and Molecular & Cellular Proteomics.
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.