Qin Yang
- Biochemistry top 0.5%
- Physiology top 1%
- Adipose Tissue and Metabolism 12
- Epidemiology top 2%
- Adipokines, Inflammation, and Metabolic Diseases 5
- Molecular Biology top 2%
- RNA and protein synthesis mechanisms 15
- DNA and Nucleic Acid Chemistry 5
- Retinoids in leukemia and cellular processes 5
- Ophthalmology top 1%
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- Bacteriophages and microbial interactions 19
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- Plant Virus Research Studies 8
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- Estrogen and related hormone effects 6
- Co-authors
- Barbara B. KahnTimothy E. GrahamNimesh ModyJanice M. ZabolotnyOdile D. PeroniLoredana QuadroFrédéric PreitnerKo Kotani
- Cited by
- BiochemistryPhysiologyEpidemiology
- Partner nations
- United StatesChinaJapan
In The Last Decade
Qin Yang
74 papers receiving 5.0k citations
Hit Papers
Peers
Comparison fields: 5 of 122
- Biochemistry 901
- Physiology 1.4k
- Epidemiology 1.6k
- Molecular Biology 2.9k
- Ophthalmology 386
Countries citing papers authored by Qin Yang
This map shows the geographic impact of Qin 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 Qin Yang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Qin Yang more than expected).
Fields of papers citing papers by Qin Yang
This network shows the impact of papers produced by Qin 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 Qin Yang. The network helps show where Qin Yang may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Qin 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
| # | Work | ||
|---|---|---|---|
| 1 | 2025 | 1 | |
| 2 | 2025 | 2 | |
| 3 | 2024 | 1 | |
| 4 | 2024 | 6 | |
| 5 | 2023 | 10 | |
| 6 | 2023 | 8 | |
| 7 | 2023 | 4 | |
| 8 | 2023 | 0 | |
| 9 | 2022 | 12 | |
| 10 | Guava Leaf Extract Attenuates Insulin Resistance via the PI3K/Akt Signaling Pathway in a Type 2 Diabetic Mouse Model | 2020 | 1 |
| 11 | 2017 | 18 | |
| 12 | 2017 | 13 | |
| 13 | 2016 | 28 | |
| 14 | Hepatic SIRT1 Attenuates Hepatic Steatosis and Controls Energy Balance in Mice by Inducing Fibroblast Growth Factor 21 | 2014 | 1 |
| 15 | 2013 | 10 | |
| 16 | 2012 | 31 | |
| 17 | Study on gene expression of metallothionein in patients suffered from coal-burnt arsenism | 2005 | 1 |
| 18 | [Effect of nm23-H1 on reversing malignant phenotype on human lung cancer cell line L9981]. | 2005 | 4 |
| 19 | 2003 | 44 | |
| 20 | 2001 | 14 |
About Qin Yang
Qin Yang is a scholar working on Ecology, Molecular Biology and Physiology, having authored 75 papers that have together received 5.1k indexed citations. Recurring topics across this work include Bacteriophages and microbial interactions (19 papers), RNA and protein synthesis mechanisms (15 papers), Adipose Tissue and Metabolism (12 papers), Plant Virus Research Studies (8 papers), Estrogen and related hormone effects (6 papers), Adipokines, Inflammation, and Metabolic Diseases (5 papers), DNA and Nucleic Acid Chemistry (5 papers) and Retinoids in leukemia and cellular processes (5 papers). The work is most often cited by research in Biochemistry (901 citations), Physiology (1.4k citations) and Epidemiology (1.6k citations). Qin Yang has collaborated with scholars based in United States, China and Japan. Frequent co-authors include Barbara B. Kahn, Timothy E. Graham, Nimesh Mody, Janice M. Zabolotny, Odile D. Peroni, Loredana Quadro, Frédéric Preitner, Ko Kotani, Carlos E. Catalano and Matthias Blüher. Their work appears in journals such as Nature, New England Journal of Medicine and Nucleic Acids Research.
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.