Dake Liu
Impact in
- Toxicology top 10%
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- Phytoestrogen effects and research
Papers in
-
- Glycosylation and Glycoproteins Research 2
- Chemical Synthesis and Analysis 2
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- Diabetes, Cardiovascular Risks, and Lipoproteins 3
- Co-authors
- Yungen Xu (2 shared papers)Lei Shi (2 shared papers)Yong‐Bing Xiang (9 shared papers)Wei Zheng (5 shared papers)Qingwen Zhang (1 shared paper)Qiuyin Cai (4 shared papers)Wanqing Wen (4 shared papers)Xiao Ou Shu (3 shared papers)
- Journals
- Cancer Epidemiology Biomarkers & Prevention (2 papers)iScience (1 paper)Organic Chemistry Frontiers (1 paper)Disease Markers (1 paper)Amino Acids (1 paper)
- Partner nations
- ChinaUnited StatesNorway
In The Last Decade
Dake Liu
22 papers receiving 544 citations
Peers
Comparison fields: 5 of 83
- Toxicology 23
- Pathology and Forensic Medicine 73
- Organic Chemistry 109
- Biochemistry 20
- Oncology 74
Countries citing papers authored by Dake Liu
This map shows the geographic impact of Dake Liu'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 Dake Liu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Dake Liu more than expected).
Fields of papers citing papers by Dake Liu
This network shows the impact of papers produced by Dake Liu. 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 Dake Liu. The network helps show where Dake Liu may publish in the future.
Co-authors
The 25 scholars most cited alongside Dake Liu, 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 23 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2017 | 119 | |
| 2 | 2007 | 92 | |
| 3 | 2015 | 65 | |
| 4 | 2007 | 51 | |
| 5 | 2010 | 46 | |
| 6 | 2002 | 44 | |
| 7 | 2005 | 23 | |
| 8 | 2021 | 22 | |
| 9 | 2019 | 19 | |
| 10 | 2021 | 12 | |
| 11 | 2022 | 10 | |
| 12 | 2022 | 9 | |
| 13 | 2022 | 9 | |
| 14 | 2008 | 8 | |
| 15 | 2021 | 8 | |
| 16 | 2021 | 6 | |
| 17 | 2022 | 5 | |
| 18 | 2019 | 3 | |
| 19 | 2023 | 3 | |
| 20 | 2004 | 2 |
About Dake Liu
Dake Liu is a scholar working on Molecular Biology, Endocrinology, Diabetes and Metabolism, Organic Chemistry, Pharmacology and Pathology and Forensic Medicine, having authored 23 papers that have together received 558 indexed citations. Recurring topics across this work include Diabetes, Cardiovascular Risks, and Lipoproteins (3 papers), Glycosylation and Glycoproteins Research (2 papers), Nutritional Studies and Diet (2 papers), Chemical Synthesis and Analysis (2 papers), Carbohydrate Chemistry and Synthesis (2 papers), Adipose Tissue and Metabolism (2 papers), Cancer Research and Treatments (2 papers) and Bacterial Genetics and Biotechnology (2 papers). The work is most often cited by research in Toxicology (23 citations), Pathology and Forensic Medicine (73 citations), Organic Chemistry (109 citations), Biochemistry (20 citations) and Oncology (74 citations). Dake Liu has collaborated with scholars based in China, United States and Norway. Frequent co-authors include Yungen Xu, Lei Shi, Yong‐Bing Xiang, Wei Zheng, Qingwen Zhang, Qiuyin Cai, Wanqing Wen, Xiao Ou Shu, Sang‐Ah Lee and Gong Yang. Their work appears in journals such as Cancer Epidemiology Biomarkers & Prevention, iScience, Organic Chemistry Frontiers, Disease Markers and Amino Acids.
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.