Lan Dai
Impact in
- Cancer Research top 10%
- MicroRNA in disease regulation
- Cancer-related molecular mechanisms research
- NF-κB Signaling Pathways
- Reproductive Medicine top 5%
- Endometriosis Research and Treatment
Papers in
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- Sphingolipid Metabolism and Signaling 10
- Retinoids in leukemia and cellular processes 5
- Protein Kinase Regulation and GTPase Signaling 3
- Cell death mechanisms and regulation 2
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- Reproductive System and Pregnancy 3
- Co-authors
- Wen Di (18 shared papers)Lihua Qiu (5 shared papers)Liankun Gu (1 shared paper)Keqi Song (7 shared papers)Pu Xia (4 shared papers)Xingchen Zhou (2 shared papers)Liying Gu (3 shared papers)Yanfei Qi (3 shared papers)
In The Last Decade
Lan Dai
37 papers receiving 713 citations
Peers
Comparison fields: 5 of 73
- Cancer Research 206
- Reproductive Medicine 106
- Obstetrics and Gynecology 47
- Immunology 122
- Molecular Biology 366
Countries citing papers authored by Lan Dai
This map shows the geographic impact of Lan Dai'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 Lan Dai with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Lan Dai more than expected).
Fields of papers citing papers by Lan Dai
This network shows the impact of papers produced by Lan Dai. 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 Lan Dai. The network helps show where Lan Dai may publish in the future.
Co-authors
The 25 scholars most cited alongside Lan Dai, 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 39 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2011 | 88 | |
| 2 | 2014 | 87 | |
| 3 | 2009 | 46 | |
| 4 | 2017 | 41 | |
| 5 | 2019 | 40 | |
| 6 | MiR-199a inhibits the angiogenic potential of endometrial stromal cells under hypoxia by targeting HIF-1α/VEGF pathway. | 2015 | 39 |
| 7 | 2020 | 37 | |
| 8 | 2020 | 34 | |
| 9 | 2015 | 28 | |
| 10 | 2013 | 28 | |
| 11 | 2013 | 28 | |
| 12 | 2014 | 28 | |
| 13 | 2013 | 26 | |
| 14 | 2013 | 25 | |
| 15 | 2019 | 21 | |
| 16 | 2016 | 19 | |
| 17 | 2019 | 17 | |
| 18 | 2023 | 15 | |
| 19 | 2021 | 11 | |
| 20 | 2021 | 10 |
About Lan Dai
Lan Dai is a scholar working on Molecular Biology, Immunology, Cell Biology, Reproductive Medicine and Hematology, having authored 39 papers that have together received 722 indexed citations. Recurring topics across this work include Sphingolipid Metabolism and Signaling (10 papers), Retinoids in leukemia and cellular processes (5 papers), Endometriosis Research and Treatment (4 papers), Caveolin-1 and cellular processes (4 papers), Reproductive System and Pregnancy (3 papers), Protein Kinase Regulation and GTPase Signaling (3 papers), Endoplasmic Reticulum Stress and Disease (2 papers) and Cell death mechanisms and regulation (2 papers). The work is most often cited by research in Cancer Research (206 citations), Reproductive Medicine (106 citations), Obstetrics and Gynecology (47 citations), Immunology (122 citations) and Molecular Biology (366 citations). Lan Dai has collaborated with scholars based in China, Australia and Ethiopia. Frequent co-authors include Wen Di, Lihua Qiu, Liankun Gu, Keqi Song, Pu Xia, Xingchen Zhou, Liying Gu, Yanfei Qi, Yuan Hu and Wenjing Wang. Their work appears in journals such as PLoS ONE, Journal of Ovarian Research, Frontiers in Pharmacology, Molecular Human Reproduction and Oncotarget.
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.