Breast cancer-derived extracellular vesicles modulate the cytoplasmic and cytoskeletal metabolism of blood-brain barrier endothelial cells

Abstract

This work utilizes machine learning analysis methods to examine cell morphology and motility features, in order to help comprehend similar or heterogeneous attributes among different cell types across various datasets.

Installation

To install necessary library packages, run the following command in your terminal:

pip install -r requirements.txt

Usage(Testing) and Note

• Clone the repo to your project folder by using the following commend:

  git clone https://github.com/kleelab-bch/Machine-Learning-Analysis

• Can directly run Main.py and the figures will be generated in Result_plot folder for testing.

• Users can modify the file path to point to their own cell feature data.

• Be sure that this work mainly works on analyzing the morphology features (10 attributes) or motility features (9 attributes) of cells.

Citation

@article{Busatto2025BreastEVs,
  author       = {Busatto, Sara and Song, Tzu‑Hsi and Kim, Hyung Joon and Hallinan, Caleb and Lombardo, Michael N. and Stemmer‑Rachamimov, Anat O. and Lee, Kwonmoo and Moses, Marsha A.},
  title        = {Breast cancer–derived extracellular vesicles modulate the cytoplasmic and cytoskeletal dynamics of blood–brain barrier endothelial cells},
  journal      = {Journal of Extracellular Vesicles},
  volume       = {14},
  number       = {1},
  pages        = {e70038},
  year         = {2025},
  doi          = {10.1002/jev2.70038},
  url          = {https://doi.org/10.1002/jev2.70038}
}

License

This project is licensed under the MIT License. Please See the LICENSE file for more details.

Contact

If you have any question about the code, please contact kwonmoo.lee@childrens.harvard.edu