Xing Yu
- Epidemiology top 2%
- Molecular Biology top 10%
- Endocrinology, Diabetes and Metabolism top 2%
- Physiology top 5%
- Surgery top 10%
- Co-authors
- Brett P. MoniaSanjay BhanotKanji YamaguchiShannon J. McCallJiawen HuangYin-xiong LiAnna Mae DiehlLiu Yang
- Topics
- Spine and Intervertebral Disc Pathology (10 papers)Adipose Tissue and Metabolism (7 papers)Musculoskeletal pain and rehabilitation (6 papers)
- Partner nations
- ChinaUnited States
In The Last Decade
Xing Yu
38 papers receiving 2.6k citations
Hit Papers
Peers
Comparison fields: 5 of 93
- Epidemiology 1.3k
- Molecular Biology 1.2k
- Endocrinology, Diabetes and Metabolism 684
- Physiology 519
- Surgery 497
Countries citing papers authored by Xing Yu
This map shows the geographic impact of Xing Yu'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 Xing Yu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Xing Yu more than expected).
Fields of papers citing papers by Xing Yu
This network shows the impact of papers produced by Xing Yu. 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 Xing Yu. The network helps show where Xing Yu may publish in the future.
Co-authorship network of co-authors of Xing Yu
This figure shows the co-authorship network connecting the top 25 collaborators of Xing Yu. A scholar is included among the top collaborators of Xing Yu based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Xing Yu. Xing Yu is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 0 | |
| 3 | 2 | |
| 4 | 11 | |
| 5 | 7 | |
| 6 | 11 | |
| 7 | 6 | |
| 8 | 5 | |
| 9 | 3 | |
| 10 | 12 | |
| 11 | 128 | |
| 12 | 25 | |
| 13 | Experiences of Professor TONG Guang-dong in Treating Nonalcoholic Fatty Liver Disease | 1 |
| 14 | Analysis of the uncertainty for the determination of iron in lubricating oil by atomic absorption spectrometry | 1 |
| 15 | 27 | |
| 16 | 15 | |
| 17 | Inhibiting triglyceride synthesis improves hepatic steatosis but exacerbates liver damage and fibrosis in obese mice with nonalcoholic steatohepatitisbreakdown → | 805 |
| 18 | 312 | |
| 19 | 481 | |
| 20 | 13 |
About Xing Yu
Xing Yu is a scholar working on Pathology and Forensic Medicine, Pharmacology and Clinical Biochemistry, having authored 39 papers that have together received 2.6k indexed citations. Recurring topics across this work include Spine and Intervertebral Disc Pathology (10 papers), Adipose Tissue and Metabolism (7 papers) and Musculoskeletal pain and rehabilitation (6 papers). The work is most often cited by research in Biochemistry (440 citations), Endocrinology, Diabetes and Metabolism (684 citations) and Epidemiology (1.3k citations). Xing Yu has collaborated with scholars based in China and United States. Frequent co-authors include Brett P. Monia, Sanjay Bhanot, Kanji Yamaguchi, Shannon J. McCall, Jiawen Huang, Yin-xiong Li, Anna Mae Diehl, Liu Yang, Sanjay Pandey and Sanjay K. Pandey. Their work appears in journals such as Proceedings of the National Academy of Sciences, Journal of Biological Chemistry 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.