SSEL-CPP: A SHAP-based feature-selection ensemble learning framework identifies molecular properties of cell-penetrating peptides.

Kwon CW, Kwon M, Basith S, Misra S, Jang YE, Lee G.

DOI: 10.1002/pro.70704
Published: 2026-08-01
Container: Protein Sci
Publisher: Not recorded
Open access: yes

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Cite this work

BibTeX

@article{allodium:10.1002/pro.70704,
  title = {SSEL-CPP: A SHAP-based feature-selection ensemble learning framework identifies molecular properties of cell-penetrating peptides.},
  author = {Kwon CW and  Kwon M and  Basith S and  Misra S and  Jang YE and  Lee G.},
  year = {2026},
  journal = {Protein Sci},
  doi = {10.1002/pro.70704},
  url = {https://doi.org/10.1002/pro.70704}
}

RIS

TY  - JOUR
TI  - SSEL-CPP: A SHAP-based feature-selection ensemble learning framework identifies molecular properties of cell-penetrating peptides.
AU  - Kwon CW
AU  -  Kwon M
AU  -  Basith S
AU  -  Misra S
AU  -  Jang YE
AU  -  Lee G.
PY  - 2026
JO  - Protein Sci
DO  - 10.1002/pro.70704
UR  - https://doi.org/10.1002/pro.70704
ER  -

APA

CW, K., M, K., S, B., S, M., YE, J., & G., L. (2026). SSEL-CPP: A SHAP-based feature-selection ensemble learning framework identifies molecular properties of cell-penetrating peptides.. Protein Sci. https://doi.org/10.1002/pro.70704

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europe-pmc · retrieved 2026-09-25T13:26:46.854Z