Mimi Wan

10.9k total citations · 5 hit papers
101 papers, 8.3k citations indexed

About

Mimi Wan is a scholar working on Biomedical Engineering, Molecular Biology and Condensed Matter Physics. According to data from OpenAlex, Mimi Wan has authored 101 papers receiving a total of 8.3k indexed citations (citations by other indexed papers that have themselves been cited), including 43 papers in Biomedical Engineering, 38 papers in Molecular Biology and 38 papers in Condensed Matter Physics. Recurrent topics in Mimi Wan's work include Micro and Nano Robotics (38 papers), Nanoplatforms for cancer theranostics (17 papers) and Molecular Communication and Nanonetworks (13 papers). Mimi Wan is often cited by papers focused on Micro and Nano Robotics (38 papers), Nanoplatforms for cancer theranostics (17 papers) and Molecular Communication and Nanonetworks (13 papers). Mimi Wan collaborates with scholars based in China, United States and Czechia. Mimi Wan's co-authors include Uta Francke, Ruthie E. Amir, Huda Y. Zoghbi, Ignatia B. Van den Veyver, Chun Mao, Jian Shen, Robert H. Crabtree, Ting Li, Qi Wang and Yueqi Yu and has published in prestigious journals such as Nature, Proceedings of the National Academy of Sciences and Journal of the American Chemical Society.

In The Last Decade

Mimi Wan

92 papers receiving 8.2k citations

Hit Papers

Rett syndrome is caused by mutations in X-linked MECP2, e... 1999 2026 2008 2017 1999 2007 2023 2024 2024 1000 2.0k 3.0k

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Mimi Wan China 37 4.4k 3.6k 1.9k 1.8k 1.3k 101 8.3k
Madeline A. Lancaster United Kingdom 35 9.2k 2.1× 1.8k 0.5× 778 0.4× 4.3k 2.4× 46 0.0× 55 13.7k
Sergiu P. Pașca United States 45 6.4k 1.5× 1.3k 0.4× 1.3k 0.7× 2.7k 1.5× 32 0.0× 84 9.9k
Hidenori Suzuki Japan 45 2.2k 0.5× 375 0.1× 492 0.3× 363 0.2× 58 0.0× 317 7.8k
Sabine Maier Germany 43 1.2k 0.3× 248 0.1× 964 0.5× 684 0.4× 97 0.1× 137 5.4k
Kazunori Nakajima Japan 57 5.9k 1.3× 1.9k 0.5× 874 0.5× 153 0.1× 80 0.1× 249 13.3k
Hiroshi Ichinose Japan 51 4.5k 1.0× 1.1k 0.3× 348 0.2× 282 0.2× 62 0.0× 268 10.8k
John W. Haycock United States 67 4.9k 1.1× 438 0.1× 879 0.5× 2.5k 1.4× 25 0.0× 234 13.9k
Evan Y. Snyder United States 61 9.5k 2.1× 1.3k 0.4× 292 0.2× 1.3k 0.7× 22 0.0× 180 17.7k
Krystof S. Bankiewicz United States 55 3.8k 0.9× 2.7k 0.7× 702 0.4× 814 0.5× 23 0.0× 153 8.4k
Dwaine F. Emerich United States 49 2.3k 0.5× 457 0.1× 462 0.2× 999 0.6× 30 0.0× 185 7.2k

Countries citing papers authored by Mimi Wan

Since Specialization
Citations

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

Fields of papers citing papers by Mimi Wan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Mimi Wan

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

All Works

20 of 20 papers shown
2.
Feng, Shibao, et al.. (2025). Application of Nanoformulations in the Treatment of Oral Cancer. Small. 21(46). e08260–e08260.
3.
Chen, Lin, et al.. (2025). Sulfur dioxide-releasing nanomotors improve the therapeutic effect of liver fibrosis by restoring the fenestrae of sinusoids. Journal of Colloid and Interface Science. 692. 137557–137557. 2 indexed citations
4.
Liu, Nian, Zhan Chen, Chun Mao, et al.. (2025). NO-releasing nanomotor-loaded microneedles induce melanoma cell death via intracellular self-assembly. International Journal of Pharmaceutics. 681. 125820–125820.
5.
Chen, Tiantian, Yu Duan, Yingjie Wang, et al.. (2025). Size-variable self-feedback nanomotors for glioblastoma therapy via mitochondrial mineralization. Nature Communications. 16(1). 8990–8990.
6.
Chen, Yidan, Yao Zhang, Yunxin Xue, et al.. (2024). Dual responsive drug-loaded nanomotor based on zwitterionic materials for the treatment of peritoneal metastatic cancer. Journal of Colloid and Interface Science. 679(Pt A). 868–878. 6 indexed citations
7.
Chen, Tiantian, et al.. (2024). Biomimetic mineralization: construction and biomedical applications of biohybrid materials. Materials Chemistry Frontiers. 8(20). 3383–3412. 5 indexed citations
8.
Wu, Ziyu, Lin Chen, Jun Wang, et al.. (2024). Oral mitochondrial transplantation using nanomotors to treat ischaemic heart disease. Nature Nanotechnology. 19(9). 1375–1385. 72 indexed citations breakdown →
9.
Gao, Zheng, Ziyu Wu, Jun Wang, et al.. (2024). Artificial Neutrophils Against Vascular Graft Infection. Advanced Science. 11(30). e2402768–e2402768. 4 indexed citations
10.
Li, Ting, Lin Chen, Yunxin Xue, et al.. (2024). Chemotactic nanomotor for multimodal combined therapy of glioblastoma. Science China Chemistry. 67(4). 1277–1288. 13 indexed citations
11.
Chen, Lin, Dan Fang, Xiangyu Xiao, et al.. (2023). Nanomotors-loaded microneedle patches for the treatment of bacterial biofilm-related infections of wound. Journal of Colloid and Interface Science. 647. 142–151. 43 indexed citations
13.
Chen, Yidan, et al.. (2023). Progress in the Treatment of Peritoneal Metastatic Cancer and the Application of Therapeutic Nanoagents. ACS Applied Bio Materials. 6(11). 4518–4548. 2 indexed citations
14.
Li, Ting, Zhiyong Liu, Jinglei Hu, et al.. (2022). A Universal Chemotactic Targeted Delivery Strategy for Inflammatory Diseases. Advanced Materials. 34(47). e2206654–e2206654. 47 indexed citations
15.
Wan, Mimi, Ting Li, Huan Chen, et al.. (2021). Zwitterion‐Based Hydrogen Sulfide Nanomotors Induce Multiple Acidosis in Tumor Cells by Destroying Tumor Metabolic Symbiosis. Angewandte Chemie International Edition. 60(29). 16139–16148. 111 indexed citations
16.
Wang, Meng, Wenqiang Yan, Dan Fang, et al.. (2020). Nanomotor-based adsorbent for blood Lead(II) removal in vitro and in pig models. Bioactive Materials. 6(4). 1140–1149. 24 indexed citations
17.
Chen, Huan, Yueqi Yu, Yangyang Huang, et al.. (2019). A dual-responsive biosensor for blood lead detection. Analytica Chimica Acta. 1093. 131–141. 30 indexed citations
18.
Zhou, Qian, Yang Liu, Yuhong Liu, et al.. (2017). Superoxide Anion Biosensor Based on Bionic-Enzyme Hyperbranched Polyester Particles. Australian Journal of Chemistry. 71(3). 119–126. 1 indexed citations
19.
Wan, Mimi & Jianhui Wang. (2014). RNA Sequencing and its Applications in Cancer Diagnosis and Targeted Therapy. North American Journal of Medicine and Science. 7(4). 4 indexed citations
20.
Lessard, Julie, Jiang Wu, Jeffrey A. Ranish, et al.. (2007). An Essential Switch in Subunit Composition of a Chromatin Remodeling Complex during Neural Development. Neuron. 55(2). 201–215. 559 indexed citations breakdown →

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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