Analysis of DNA methylation patterns in cancer samples using SOM

  1. Diaz-Blanco, Ignacio 1
  2. Enguita-Gonzalez, Jose M. 1
  3. Garcia-Perez, Diego 1
  4. Cuadrado-Vega, Abel A. 1
  5. Valdes-Gallego, Nuria
  6. Chiara-Romero, Maria Dolores 1
  1. 1 Universidad de Oviedo
    info

    Universidad de Oviedo

    Oviedo, España

    ROR https://ror.org/006gksa02

Actas:
European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning, ESANN 2024

Ano de publicación: 2024

Páxinas: 715-720

Congreso: European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (32th. 2024. Bruges, Bélgica)

Tipo: Achega congreso

DOI: 10.14428/ESANN/2024.ES2024-42 GOOGLE SCHOLAR lock_openAcceso aberto editor

Resumo

By leveraging the SOM algorithm and the extensive epigenomic data from TCGA, this work aims to suggest a valid approach to explore the relationships between epigenetic alterations and PCPG pathogenesis. Additionally, the methodological approach presented here lays the foundation for a potentially valuable analysis tool that can be applied to other cancer types and epigenetic research.

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Información de financiamento

This work is part of Grant PID2020-115401GB-I00 funded by MCIN/AEI/ 10.13039/501100011033.

Financiadores