Comparación de modelos de aprendizaje automático para la predicción de células cancerígenas a partir del complejo MHC I Thesis

short description

  • Undergraduate thesis

Thesis author

  • Navas Luquez, Mateo

abstract

  • The present work proposes a comparison of machine learning models for the detection of cancer cells from the MHC I complex antigens. Using protocols for the extraction of physical-chemical characteristics of proteins and a comparative process of performance measurements in the model validation and testing phase. This procedure aims to determine the machine learning model presenting the best performance in the prediction of carcinogenic antigens, using physicochemical properties as input markers.

publication date

  • May 27, 2020 9:38 PM

keywords

  • Antigen
  • Cancer
  • Machine Learning

Document Id

  • 2e632c77-3e07-4c39-b281-bb868a1d52df