|
Title:
|
Pipeline design to identify key features and perform classification on response/predisposition large-scale genetic data
|
|
Author:
|
Valdés Graterol, María Gabriela
|
|
Other authors:
|
Universitat Politècnica de Catalunya. Departament de Ciències de la Computació; Gavaldà Mestre, Ricard; Palou, Xavier Rafael |
|
Abstract:
|
We propose a state-of-the-art, scalable and flexible alternative to the classical GWAS approach, based on machine learning techniques, to analyze large-scale data and discover epistatic and non-epistatic polygenic variants in complex diseases. |
|
Subject(s):
|
-Àrees temàtiques de la UPC::Informàtica
-Machine learning
-Data analysis
-missing heritability
-GWAS
-SNP
-feature selection
-sampling
-classification.
-Aprenentatge automàtic
-Anàlisi de dades |
|
Rights:
|
|
|
Document type:
|
Research/Master Thesis |
|
Published by:
|
Universitat Politècnica de Catalunya
|
|
Share:
|
|
