GASVeM: A New Machine Learning Methodology for Multi-SNP Analysis of GWAS Data Based on Genetic Algorithms and Support Vector Machines

GASVeM: A New Machine Learning Methodology for Multi-SNP Analysis of GWAS Data Based on Genetic Algorithms and Support Vector Machines

Genome-wide association studies (GWAS) are observational studies of a large set of genetic variants in an individual’s sample in order to find if any of these variants are linked to a particular trait. In the last two decades, GWAS have contributed to several new discoveries in the field of genetics...

Full description

Bibliographic Details
Main Authors: Fidel Díez Díaz, Fernando Sánchez Lasheras, Víctor Moreno, Ferran Moratalla-Navarro, Antonio José Molina de la Torre, Vicente Martín Sánchez
Format: Article
Language:English
Published: MDPI AG 2021-03-01
Series:Mathematics
Subjects:
machine learning
support vector machines
genetic algorithms
genome-wide association studies
single nucleotide polymorphism
pathways analysis
Online Access:https://www.mdpi.com/2227-7390/9/6/654

Internet

https://www.mdpi.com/2227-7390/9/6/654

Similar Items