Machine learning of performance space mapping for the DPD simulation of drug delivery to endothelial cells-Reference-Cited by-同舟云学术

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Machine learning of performance space mapping for the DPD simulation of drug delivery to endothelial cells

Published:2024-04-05 Issue:10 Volume:50 Page:622-630
ISSN:0892-7022
Container-title:Molecular Simulation
language:en
Short-container-title:Molecular Simulation

Author:

Akbarishandiz Saeed¹,Ray Soumya²,Zhou Fei³,Chen Xiao³,Maia Joao¹

Affiliation:

1. Department of Macromolecular Science and Engineering, Case Western Reserve University, Cleveland, OH, USA

2. Department of Electrical Engineering and Computer Science, Case Western Reserve University, Cleveland, OH, USA

3. Lawrence Livermore National Lab, Livermore, CA, USA

Funder

NSF

Publisher

Informa UK Limited

Link

https://www.tandfonline.com/doi/pdf/10.1080/08927022.2024.2333903

Reference43 articles.

1. Biodistribution and clearance of a filamentous plant virus in healthy and tumor-bearing mice

2. Design rules for nanomedical engineering: from physical virology to the applications of virus-based materials in medicine

3. Effect of ligand density, receptor density, and nanoparticle size on cell targeting

4. Endothelial Targeting of High-Affinity Multivalent Polymer Nanocarriers Directed to Intercellular Adhesion Molecule 1

Cited by 1 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Adhesion dynamics of Janus nanocarriers to endothelial cells: A dissipative particle dynamics study;Physical Review E;2024-06-18

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