A robust and stable gene selection algorithm based on graph theory and machine learning

Abstract Background Nowadays we are observing an explosion of gene expression data with phenotypes. It enables us to accurately identify genes responsible for certain medical condition as well as classify them for drug target. Like any other phenotype data in medical domain, gene expression data wit...

Descripción completa

Guardado en:

Detalles Bibliográficos
Autores principales:	Subrata Saha, Ahmed Soliman, Sanguthevar Rajasekaran
Formato:	article
Lenguaje:	EN
Publicado:	BMC 2021
Materias:	Robust and Stable Gene Selection Algorithm (RSGSA) Symmetric Uncertainty (SU) Gain ratio (GR) Support vector machine-recursive feature elimination (SVM-RFE) Linear Support Vector Machine (LSVM) Medicine R Genetics QH426-470
Acceso en línea:	https://doaj.org/article/21e4f9da095a4dce8150adf6a5967f79
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

Sea el primero en dejar un comentario!

A robust and stable gene selection algorithm based on graph theory and machine learning

Ejemplares similares