Network Pharmacology and Machine Learning Identify Flavonoids as Potential Senotherapeutics

Jose Alberto Santiago-de-la-Cruz, Nadia Alejandra Rivero-Segura, María Elizbeth Alvarez-Sánchez, Juan Carlos Gomez-Verjan

Open source

DOI
10.3390/ph18081176
Published
2025-08-09
Container
Pharmaceuticals
Publisher
MDPI AG
Open access
unknown

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BibTeX

@article{allodium:10.3390/ph18081176,
  title = {Network Pharmacology and Machine Learning Identify Flavonoids as Potential Senotherapeutics},
  author = {Jose Alberto Santiago-de-la-Cruz and Nadia Alejandra Rivero-Segura and María Elizbeth Alvarez-Sánchez and Juan Carlos Gomez-Verjan},
  year = {2025},
  journal = {Pharmaceuticals},
  doi = {10.3390/ph18081176},
  url = {https://doi.org/10.3390/ph18081176}
}

RIS

TY  - JOUR
TI  - Network Pharmacology and Machine Learning Identify Flavonoids as Potential Senotherapeutics
AU  - Jose Alberto Santiago-de-la-Cruz
AU  - Nadia Alejandra Rivero-Segura
AU  - María Elizbeth Alvarez-Sánchez
AU  - Juan Carlos Gomez-Verjan
PY  - 2025
JO  - Pharmaceuticals
DO  - 10.3390/ph18081176
UR  - https://doi.org/10.3390/ph18081176
ER  - 

APA

Santiago-de-la-Cruz, J. A., Rivero-Segura, N. A., Alvarez-Sánchez, M. E., & Gomez-Verjan, J. C. (2025). Network Pharmacology and Machine Learning Identify Flavonoids as Potential Senotherapeutics. Pharmaceuticals. https://doi.org/10.3390/ph18081176

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