Algoritmos Evolutivos Multiobjetivo aplicados a la Selección de Características en Microarrays de Datos de Cáncer

  • Julieta Sol Dussaut Universidad Nacional del Sur
  • Ignacio Ponzoni Universidad Nacional del Sur
  • Ana Carolina Olivera Universidad Nacional de Cuyo
  • Pablo Javier Vidal Universidad Nacional de Cuyo
Palabras clave: Algoritmos Evolutivos Multiobjetivo, Expresión de genes, Microarrays de Cáncer, Selección de características

Resumen

El análisis de microarrays de expresión de genes es un tópico actual para el diagnóstico y clasificación del cáncer humano. Un microarray de datos de expresión de genes consiste en una matriz de miles de características de las cuales la mayoría es irrelevante para clasificar patrones de expresiones de genes. La elección de un subconjunto mínimo de características para clasificación es una tarea dificultosa. En este trabajo, se realiza una comparación entre dos algoritmos evolutivos multiobjetivo aplicados a conjuntos de expresiones de genes populares en la literatura (linfoma, leucemia y colon). Con el objetivo de remover las características con fuerte correlación se realiza una etapa de pre-procesamiento. Se muestra un análisis extenso y detallado de los resultados obtenidos para los algoritmos multiobjetivo seleccionados.

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Publicado
2020-12-31
Cómo citar
Dussaut, J., Ponzoni, I., Olivera, A., & Vidal, P. (2020). Algoritmos Evolutivos Multiobjetivo aplicados a la Selección de Características en Microarrays de Datos de Cáncer. Entre Ciencia E Ingeniería, 14(28), 40-45. https://doi.org/10.31908/19098367.2014
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