Bingmei M. Fu

4.6k total citations
124 papers, 3.6k citations indexed

About

Bingmei M. Fu is a scholar working on Molecular Biology, Neurology and Pulmonary and Respiratory Medicine. According to data from OpenAlex, Bingmei M. Fu has authored 124 papers receiving a total of 3.6k indexed citations (citations by other indexed papers that have themselves been cited), including 36 papers in Molecular Biology, 33 papers in Neurology and 26 papers in Pulmonary and Respiratory Medicine. Recurrent topics in Bingmei M. Fu's work include Blood properties and coagulation (24 papers), Barrier Structure and Function Studies (24 papers) and Angiogenesis and VEGF in Cancer (20 papers). Bingmei M. Fu is often cited by papers focused on Blood properties and coagulation (24 papers), Barrier Structure and Function Studies (24 papers) and Angiogenesis and VEGF in Cancer (20 papers). Bingmei M. Fu collaborates with scholars based in United States, China and Hong Kong. Bingmei M. Fu's co-authors include John M. Tarbell, Min Zeng, Ye Zeng, Jie Fan, Guanglei Li, Wei Yuan, Yang Liu, Bin Cai, Sheldon Weinbaum and F. E. Curry and has published in prestigious journals such as PLoS ONE, Scientific Reports and The FASEB Journal.

In The Last Decade

Bingmei M. Fu

119 papers receiving 3.5k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Bingmei M. Fu United States 36 1.0k 695 619 589 549 124 3.6k
F. E. Curry United States 46 2.1k 2.0× 560 0.8× 740 1.2× 963 1.6× 936 1.7× 105 5.6k
C. C. Michel United Kingdom 38 1.3k 1.2× 566 0.8× 431 0.7× 1.2k 2.0× 880 1.6× 99 5.4k
Geert W. Schmid‐Schönbein United States 53 1.9k 1.8× 866 1.2× 728 1.2× 1.2k 2.0× 940 1.7× 177 8.9k
Virginia H. Huxley United States 33 1.0k 1.0× 407 0.6× 188 0.3× 361 0.6× 324 0.6× 93 3.2k
Dick W. Slaaf Netherlands 37 884 0.8× 521 0.7× 218 0.4× 864 1.5× 537 1.0× 146 5.5k
Ruben M. Sandoval United States 43 1.8k 1.7× 508 0.7× 133 0.2× 412 0.7× 318 0.6× 110 5.5k
Jahar Bhattacharya United States 45 2.8k 2.6× 634 0.9× 210 0.3× 3.1k 5.3× 477 0.9× 122 7.6k
Ming Zhao China 36 2.6k 2.5× 493 0.7× 272 0.4× 255 0.4× 257 0.5× 170 5.2k
Ralph A. Schmid Switzerland 47 2.0k 1.9× 942 1.4× 292 0.5× 3.6k 6.2× 281 0.5× 296 8.7k
K. Meßmer Germany 41 705 0.7× 461 0.7× 86 0.1× 543 0.9× 225 0.4× 138 5.1k

Countries citing papers authored by Bingmei M. Fu

Since Specialization
Citations

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

Fields of papers citing papers by Bingmei M. Fu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Bingmei M. Fu. 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 Bingmei M. Fu. The network helps show where Bingmei M. Fu may publish in the future.

Co-authorship network of co-authors of Bingmei M. Fu

This figure shows the co-authorship network connecting the top 25 collaborators of Bingmei M. Fu. A scholar is included among the top collaborators of Bingmei M. Fu 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 Bingmei M. Fu. Bingmei M. Fu 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
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Wu, Liyuan, et al.. (2024). Multi-omics analysis unveils early molecular responses to aluminum toxicity in barley root tip. Plant Physiology and Biochemistry. 217. 109209–109209. 3 indexed citations
4.
Xia, Yifan, Yunfei Li, & Bingmei M. Fu. (2022). Differential effects of vascular endothelial growth factor on glycocalyx of endothelial and tumor cells and potential targets for tumor metastasis. APL Bioengineering. 6(1). 16101–16101. 11 indexed citations
5.
Liu, Yang, et al.. (2022). A three-dimensional simulation of the dynamics of primary cilia in an oscillating flow. Applied Mathematical Modelling. 108. 825–839. 7 indexed citations
6.
Xia, Yifan, Huixiang Zhu, Yan Sun, et al.. (2021). Investigation of Neurodevelopmental Deficits of 22 q11.2 Deletion Syndrome with a Patient-iPSC-Derived Blood–Brain Barrier Model. Cells. 10(10). 2576–2576. 14 indexed citations
7.
Chi, Chun‐Wei, et al.. (2020). High‐Throughput Tumor‐on‐a‐Chip Platform to Study Tumor–Stroma Interactions and Drug Pharmacokinetics. Advanced Healthcare Materials. 9(21). e2000880–e2000880. 41 indexed citations
8.
Zhang, Lin, et al.. (2020). Transcellular Model for Neutral and Charged Nanoparticles Across an In Vitro Blood–Brain Barrier. Cardiovascular Engineering and Technology. 11(6). 607–620. 34 indexed citations
9.
Fu, Bingmei M.. (2018). Transport Across the Blood-Brain Barrier. Advances in experimental medicine and biology. 1097. 235–259. 47 indexed citations
10.
Xia, Yifan & Bingmei M. Fu. (2018). Investigation of Endothelial Surface Glycocalyx Components and Ultrastructure by Single Molecule Localization Microscopy: Stochastic Optical Reconstruction Microscopy (STORM).. PubMed. 91(3). 257–266. 18 indexed citations
11.
Liu, Yang, et al.. (2017). Dissipative particle dynamics simulation of multiple deformable red blood cells in a vessel. International Journal of Computational Methods and Experimental Measurements. 6(2). 303–313. 2 indexed citations
12.
Song, Jong Wook, Joseph Zullo, Mark Lipphardt, et al.. (2017). Endothelial glycocalyx—the battleground for complications of sepsis and kidney injury. Nephrology Dialysis Transplantation. 33(2). 203–211. 32 indexed citations
13.
Dragovich, Matthew A., Daniel Chester, Bingmei M. Fu, et al.. (2016). Mechanotransduction of the endothelial glycocalyx mediates nitric oxide production through activation of TRP channels. American Journal of Physiology-Cell Physiology. 311(6). C846–C853. 68 indexed citations
14.
Khadka, Niranjan, et al.. (2016). Transcranial direct current stimulation transiently increases the blood-brain barrier solute permeability in vivo. Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE. 9788. 97881X–97881X. 4 indexed citations
15.
Fu, Bingmei M., et al.. (2015). Reinforcing endothelial junctions prevents microvessel permeability increase and tumor cell adhesion in microvessels in vivo. Scientific Reports. 5(1). 15697–15697. 22 indexed citations
16.
Wei, Jie, Bin Cai, Lin Zhang, & Bingmei M. Fu. (2014). Automatic Classification and Quantification of Cell Adhesion Locations on the Endothelium. Annals of Biomedical Engineering. 43(8). 1803–1814. 4 indexed citations
17.
Shi, Lingyan, Min Zeng, & Bingmei M. Fu. (2014). Temporal effects of vascular endothelial growth factor and 3,5‐cyclic monophosphate on blood–brain barrier solute permeability in vivo. Journal of Neuroscience Research. 92(12). 1678–1689. 17 indexed citations
18.
Zeng, Ye, Eno E. Ebong, Bingmei M. Fu, & John M. Tarbell. (2012). The Structural Stability of the Endothelial Glycocalyx after Enzymatic Removal of Glycosaminoglycans. PLoS ONE. 7(8). e43168–e43168. 105 indexed citations
19.
Yuan, Wei, Yonggang Lv, Min Zeng, & Bingmei M. Fu. (2008). Non-invasive measurement of solute permeability in cerebral microvessels of the rat. Microvascular Research. 77(2). 166–173. 145 indexed citations
20.
Fu, Bingmei M., et al.. (2004). VEGF-Induced Microvessel Hyperpermeability Increases Cancer Cell Adhesion in Vivo. The FASEB Journal. 18(4).

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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