Luan Wen
Impact in
- Aging top 10%
-
- Thyroid Disorders and Treatments
- Growth Hormone and Insulin-like Growth Factors
Papers in
-
- CRISPR and Genetic Engineering 10
- Renal and related cancers 4
- Epigenetics and DNA Methylation 4
- Pluripotent Stem Cells Research 4
- Genetics 13
- Genetic and Clinical Aspects of Sex Determination and Chromosomal Abnormalities 4
- Co-authors
- Yun‐Bo Shi (13 shared papers)Liezhen Fu (7 shared papers)Morihiro Okada (3 shared papers)Yuki Shibata (2 shared papers)Thomas C. R. Miller (3 shared papers)Dan Su (2 shared papers)Yonglong Chen (4 shared papers)Jie Xu (5 shared papers)
- Journals
- Cell & Bioscience (4 papers)Endocrinology (4 papers)Stem Cell Research (3 papers)The FASEB Journal (2 papers)Scientific Reports (1 paper)
- Partner nations
- United StatesChinaHong Kong
In The Last Decade
Luan Wen
30 papers receiving 588 citations
Peers
Comparison fields: 5 of 85
- Aging 22
- Endocrinology, Diabetes and Metabolism 182
- Genetics 206
- Business and International Management 12
- Molecular Biology 302
Countries citing papers authored by Luan Wen
This map shows the geographic impact of Luan Wen'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 Luan Wen with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Luan Wen more than expected).
Fields of papers citing papers by Luan Wen
This network shows the impact of papers produced by Luan Wen. 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 Luan Wen. The network helps show where Luan Wen may publish in the future.
Co-authors
The 25 scholars most cited alongside Luan Wen, 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 32 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2014 | 75 | |
| 2 | 2017 | 49 | |
| 3 | 2021 | 45 | |
| 4 | 2015 | 42 | |
| 5 | 2020 | 38 | |
| 6 | 2021 | 33 | |
| 7 | 2019 | 31 | |
| 8 | 2020 | 28 | |
| 9 | 2015 | 25 | |
| 10 | 2014 | 25 | |
| 11 | 2015 | 20 | |
| 12 | 2017 | 19 | |
| 13 | 2016 | 18 | |
| 14 | 2010 | 16 | |
| 15 | 2022 | 15 | |
| 16 | 2019 | 14 | |
| 17 | 2013 | 13 | |
| 18 | 2012 | 11 | |
| 19 | 2014 | 11 | |
| 20 | 2017 | 11 |
About Luan Wen
Luan Wen is a scholar working on Molecular Biology, Genetics, Endocrinology, Diabetes and Metabolism, Surgery and Plant Science, having authored 32 papers that have together received 592 indexed citations. Recurring topics across this work include CRISPR and Genetic Engineering (10 papers), Thyroid Disorders and Treatments (6 papers), Renal and related cancers (4 papers), Genetic and Clinical Aspects of Sex Determination and Chromosomal Abnormalities (4 papers), Epigenetics and DNA Methylation (4 papers), Growth Hormone and Insulin-like Growth Factors (4 papers), Pluripotent Stem Cells Research (4 papers) and Pancreatic function and diabetes (3 papers). The work is most often cited by research in Aging (22 citations), Endocrinology, Diabetes and Metabolism (182 citations), Genetics (206 citations), Business and International Management (12 citations) and Molecular Biology (302 citations). Luan Wen has collaborated with scholars based in United States, China and Hong Kong. Frequent co-authors include Yun‐Bo Shi, Liezhen Fu, Morihiro Okada, Yuki Shibata, Thomas C. R. Miller, Dan Su, Yonglong Chen, Jie Xu, Y. Eugene Chen and Jinxue Ruan. Their work appears in journals such as Cell & Bioscience, Endocrinology, Stem Cell Research, The FASEB Journal and Scientific Reports.
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.