Ning Wang

20.6k total citations · 5 hit papers
115 papers, 15.3k citations indexed

About

Ning Wang is a scholar working on Cell Biology, Biomedical Engineering and Molecular Biology. According to data from OpenAlex, Ning Wang has authored 115 papers receiving a total of 15.3k indexed citations (citations by other indexed papers that have themselves been cited), including 99 papers in Cell Biology, 40 papers in Biomedical Engineering and 30 papers in Molecular Biology. Recurrent topics in Ning Wang's work include Cellular Mechanics and Interactions (96 papers), 3D Printing in Biomedical Research (30 papers) and Force Microscopy Techniques and Applications (29 papers). Ning Wang is often cited by papers focused on Cellular Mechanics and Interactions (96 papers), 3D Printing in Biomedical Research (30 papers) and Force Microscopy Techniques and Applications (29 papers). Ning Wang collaborates with scholars based in United States, China and Croatia. Ning Wang's co-authors include Donald E. Ingber, James P. Butler, Dimitrije Stamenović, Jessica Tytell, Jeffrey J. Fredberg, Farhan Chowdhury, Iva M. Tolić, Jianxin Chen, Sungsoo Na and Deborah Leckband and has published in prestigious journals such as Science, Proceedings of the National Academy of Sciences and Nature Communications.

In The Last Decade

Ning Wang

108 papers receiving 14.9k citations

Hit Papers

Mechanotransduction Across the Cell Surface and Through t... 1993 2026 2004 2015 1993 2008 2001 2002 2014 500 1000 1.5k 2.0k

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Ning Wang United States 60 9.9k 5.5k 4.6k 2.0k 1.6k 115 15.3k
Xavier Trepat Spain 65 11.1k 1.1× 6.7k 1.2× 4.2k 0.9× 1.8k 0.9× 1.5k 0.9× 136 16.1k
Ben Fabry Germany 69 8.1k 0.8× 5.9k 1.1× 2.4k 0.5× 2.4k 1.2× 1.1k 0.7× 186 14.3k
Alexander D. Bershadsky Israel 61 13.0k 1.3× 5.0k 0.9× 5.9k 1.3× 2.5k 1.2× 1.1k 0.7× 135 18.0k
Micah Dembo United States 53 10.2k 1.0× 6.6k 1.2× 3.8k 0.8× 2.4k 1.2× 977 0.6× 103 17.0k
Pere Roca‐Cusachs Spain 42 7.5k 0.8× 3.2k 0.6× 3.3k 0.7× 1.8k 0.9× 1.0k 0.6× 81 10.8k
Clare M. Waterman United States 79 13.7k 1.4× 3.8k 0.7× 8.0k 1.7× 2.0k 1.0× 1.2k 0.7× 149 20.3k
Viola Vogel Switzerland 75 7.6k 0.8× 5.2k 1.0× 6.3k 1.4× 3.8k 1.9× 724 0.4× 264 19.0k
Guillaume Charras United Kingdom 54 7.6k 0.8× 3.4k 0.6× 3.9k 0.9× 1.4k 0.7× 902 0.6× 118 12.1k
Cynthia A. Reinhart‐King United States 55 6.7k 0.7× 5.1k 0.9× 3.5k 0.7× 642 0.3× 820 0.5× 142 12.5k
Yu‐li Wang United States 41 8.2k 0.8× 4.3k 0.8× 2.9k 0.6× 1.4k 0.7× 486 0.3× 66 10.3k

Countries citing papers authored by Ning Wang

Since Specialization
Citations

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

Fields of papers citing papers by Ning Wang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Ning Wang

This figure shows the co-authorship network connecting the top 25 collaborators of Ning Wang. A scholar is included among the top collaborators of Ning Wang 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 Ning Wang. Ning Wang 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
1.
Wang, Ning, et al.. (2025). Strong Bioadhesives from Helical Polypeptides. ACS Macro Letters. 14(3). 299–305.
2.
Chen, Xinman, et al.. (2025). Three-dimensional traction technology and its application in mechanomedicine. PubMed. 3(3). 100131–100131.
3.
Wang, Ning, Liqi Chen, Shiqi Wang, et al.. (2025). Marine-inspired self-assembled peptide hydrogel spatiotemporal treatment of bacterial-infected wounds. Chemical Engineering Journal. 519. 165573–165573. 1 indexed citations
4.
Wang, Ning, Shu Chien, & Martin A. Schwartz. (2025). Mechanomedicine: Present state and future promise. Proceedings of the National Academy of Sciences. 122(46). e2509566122–e2509566122.
5.
Di, Guilan, et al.. (2023). Molecular characterization of Rab5A, and involvement in innate immunity in Yellow River Carp Cyprinus carpio. Aquaculture International. 32(2). 1427–1451. 2 indexed citations
6.
Yavitt, F. Max, Bruce E. Kirkpatrick, Michael R. Blatchley, et al.. (2023). In situ modulation of intestinal organoid epithelial curvature through photoinduced viscoelasticity directs crypt morphogenesis. Science Advances. 9(3). eadd5668–eadd5668. 59 indexed citations
7.
Mohagheghian, Erfan, Junyu Luo, F. Max Yavitt, et al.. (2023). Quantifying stiffness and forces of tumor colonies and embryos using a magnetic microrobot. Science Robotics. 8(74). eadc9800–eadc9800. 33 indexed citations
9.
Liu, Yuying, Tianzhen Zhang, Haizeng Zhang, et al.. (2020). Cell Softness Prevents Cytolytic T-cell Killing of Tumor-Repopulating Cells. Cancer Research. 81(2). 476–488. 88 indexed citations
10.
Wei, Fuxiang, et al.. (2020). Stress fiber anisotropy contributes to force-mode dependent chromatin stretching and gene upregulation in living cells. Nature Communications. 11(1). 4902–4902. 46 indexed citations
11.
Huang, Wei, Hui Hu, Qiong Zhang, et al.. (2019). Regulatory networks in mechanotransduction reveal key genes in promoting cancer cell stemness and proliferation. Oncogene. 38(42). 6818–6834. 32 indexed citations
12.
Liu, Yuying, Jiadi Lv, Xiaoyu Liang, et al.. (2018). Fibrin Stiffness Mediates Dormancy of Tumor-Repopulating Cells via a Cdc42-Driven Tet2 Epigenetic Program. Cancer Research. 78(14). 3926–3937. 88 indexed citations
13.
Chen, Junwei, Xin Cao, Quanlin An, et al.. (2018). Inhibition of cancer stem cell like cells by a synthetic retinoid. Nature Communications. 9(1). 1406–1406. 56 indexed citations
14.
Muhamed, Ismaeel, Jun Wu, Xinyu Kong, et al.. (2016). E-cadherin-mediated force transduction signals regulate global cell mechanics. Journal of Cell Science. 129(9). 1843–1854. 75 indexed citations
15.
Liu, Jing, Youhua Tan, Huafeng Zhang, et al.. (2012). Soft fibrin gels promote selection and growth of tumorigenic cells. Nature Materials. 11(8). 734–741. 384 indexed citations
16.
Uda, Yuhei, Yeh-Chuin Poh, Farhan Chowdhury, et al.. (2011). Force via integrins but not E-cadherin decreases Oct3/4 expression in embryonic stem cells. Biochemical and Biophysical Research Communications. 415(2). 396–400. 30 indexed citations
17.
Na, Sungsoo, Olivier Collin, Farhan Chowdhury, et al.. (2008). Rapid signal transduction in living cells is a unique feature of mechanotransduction. Proceedings of the National Academy of Sciences. 105(18). 6626–6631. 344 indexed citations
18.
Lele, Tanmay P., Julia Sero, Benjamin D. Matthews, et al.. (2007). Tools to Study Cell Mechanics and Mechanotransduction. Methods in cell biology. 83. 441–472. 46 indexed citations
19.
Rosenblatt, Noah J., Shaohua Hu, Jianxin Chen, Ning Wang, & Dimitrije Stamenović. (2004). Distending stress of the cytoskeleton is a key determinant of cell rheological behavior. Biochemical and Biophysical Research Communications. 321(3). 617–622. 32 indexed citations
20.
Wang, Ning. (1998). Mechanical Interactions Among Cytoskeletal Filaments. Hypertension. 32(1). 162–165. 121 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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