Mengling Yan

948 total citations · 1 hit paper
9 papers, 799 citations indexed

About

Mengling Yan is a scholar working on Molecular Biology, Nutrition and Dietetics and Developmental Neuroscience. According to data from OpenAlex, Mengling Yan has authored 9 papers receiving a total of 799 indexed citations (citations by other indexed papers that have themselves been cited), including 3 papers in Molecular Biology, 3 papers in Nutrition and Dietetics and 3 papers in Developmental Neuroscience. Recurrent topics in Mengling Yan's work include Selenium in Biological Systems (3 papers), Paraquat toxicity studies and treatments (2 papers) and Mercury impact and mitigation studies (2 papers). Mengling Yan is often cited by papers focused on Selenium in Biological Systems (3 papers), Paraquat toxicity studies and treatments (2 papers) and Mercury impact and mitigation studies (2 papers). Mengling Yan collaborates with scholars based in China, South Korea and United States. Mengling Yan's co-authors include Jun Yin, Jianzhong Fu, Yancheng Wang, Hongli Suo, Hairui Suo, Liang Li, Jingyi Liu, Zhijun Zhou, Xiuli Chang and Lina Zhao and has published in prestigious journals such as ACS Applied Materials & Interfaces, International Journal of Molecular Sciences and Food and Chemical Toxicology.

In The Last Decade

Mengling Yan

9 papers receiving 787 citations

Hit Papers

3D Bioprinting of Low-Concentration Cell-Laden Gelatin Me... 2018 2026 2020 2023 2018 100 200 300 400 500

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Mengling Yan China 8 600 322 123 99 94 9 799
Sarah Bertlein Germany 6 424 0.7× 238 0.7× 127 1.0× 71 0.7× 49 0.5× 10 579
Sarah Duin Germany 10 515 0.9× 268 0.8× 117 1.0× 78 0.8× 90 1.0× 16 680
Mingen Xu China 17 664 1.1× 262 0.8× 177 1.4× 139 1.4× 123 1.3× 45 919
Semra Ünal Türkiye 12 346 0.6× 84 0.3× 291 2.4× 79 0.8× 76 0.8× 23 643
Ali Valiani Iran 15 265 0.4× 89 0.3× 151 1.2× 129 1.3× 86 0.9× 42 613
Sieger Henke Netherlands 11 294 0.5× 91 0.3× 73 0.6× 39 0.4× 65 0.7× 17 420
Samuel R. Moxon United Kingdom 7 338 0.6× 140 0.4× 104 0.8× 81 0.8× 63 0.7× 14 453
Birgit Goversen Netherlands 6 258 0.4× 114 0.4× 78 0.6× 190 1.9× 75 0.8× 11 510

Countries citing papers authored by Mengling Yan

Since Specialization
Citations

This map shows the geographic impact of Mengling Yan'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 Mengling Yan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Mengling Yan more than expected).

Fields of papers citing papers by Mengling Yan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Mengling Yan. 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 Mengling Yan. The network helps show where Mengling Yan may publish in the future.

Co-authorship network of co-authors of Mengling Yan

This figure shows the co-authorship network connecting the top 25 collaborators of Mengling Yan. A scholar is included among the top collaborators of Mengling Yan 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 Mengling Yan. Mengling Yan is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

9 of 9 papers shown
1.
Liu, Jingyi, Liang Li, Hairui Suo, et al.. (2019). 3D printing of biomimetic multi-layered GelMA/nHA scaffold for osteochondral defect repair. Materials & Design. 171. 107708–107708. 156 indexed citations
2.
Xiong, Guiya, et al.. (2019). N‐acetylcysteine alleviated paraquat‐induced mitochondrial fragmentation and autophagy in primary murine neural progenitor cells. Journal of Applied Toxicology. 39(11). 1557–1567. 17 indexed citations
3.
Zhao, Lina, Mengling Yan, Guiya Xiong, et al.. (2018). Modification of Wnt signaling pathway on paraquat-induced inhibition of neural progenitor cell proliferation. Food and Chemical Toxicology. 121. 311–325. 15 indexed citations
4.
Yin, Jun, Mengling Yan, Yancheng Wang, Jianzhong Fu, & Hongli Suo. (2018). 3D Bioprinting of Low-Concentration Cell-Laden Gelatin Methacrylate (GelMA) Bioinks with a Two-Step Cross-linking Strategy. ACS Applied Materials & Interfaces. 10(8). 6849–6857. 502 indexed citations breakdown →
5.
Yan, Mengling, et al.. (2017). Integrated analysis of paraquat-induced microRNAs-mRNAs changes in human neural progenitor cells. Toxicology in Vitro. 44. 196–205. 9 indexed citations
6.
Yan, Mengling, Lina Zhao, Qing Wu, et al.. (2016). Low‐Dose Methylmercury‐Induced Apoptosis and Mitochondrial DNA Mutation in Human Embryonic Neural Progenitor Cells. Oxidative Medicine and Cellular Longevity. 2016(1). 5137042–5137042. 23 indexed citations
7.
Yan, Mengling, Lina Zhao, Qing Wu, et al.. (2016). Low-Dose Methylmercury-Induced Genes Regulate Mitochondrial Biogenesis via miR-25 in Immortalized Human Embryonic Neural Progenitor Cells. International Journal of Molecular Sciences. 17(12). 2058–2058. 20 indexed citations
8.
Yan, Mengling, Lina Zhao, Dan Lou, et al.. (2015). Nrf2/ARE Pathway Involved in Oxidative Stress Induced by Paraquat in Human Neural Progenitor Cells. Oxidative Medicine and Cellular Longevity. 2016(1). 8923860–8923860. 52 indexed citations
9.
Yan, Mengling, et al.. (2015). [The effect of Wnt signaling pathway on paraquat induced PC12 cells damage].. PubMed. 33(11). 806–11. 5 indexed citations

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.

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