Please use this identifier to cite or link to this item: http://hdl.handle.net/2445/184242
Title: Multivariate Analysis and Modelling of multiple Brain endOphenotypes: Let's MAMBO!
Author: Vilor-Tejedor, Natalia
Garrido Martín, Diego, 1992-
Rodríguez-Fernández, Blanca
Lamballais, Sander
Guigó Serra, Roderic
Gispert, Juan Domingo
Keywords: Genètica
Cervell
Diagnòstic per la imatge
Genetics
Brain
Diagnostic imaging
Issue Date: 28-Oct-2021
Publisher: Elsevier B.V.
Abstract: Imaging genetic studies aim to test how genetic information influences brain structure and function by combining neuroimaging-based brain features and genetic data from the same individual. Most studies focus on individual correlation and association tests between genetic variants and a single measurement of the brain. Despite the great success of univariate approaches, given the capacity of neu- roimaging methods to provide a multiplicity of cerebral phenotypes, the development and application of multivariate methods become crucial. In this article, we review novel methods and strategies focused on the analysis of multiple phenotypes and genetic data. We also discuss relevant aspects of multi-trait modelling in the context of neuroimag- ing data.
Note: Reproducció del document publicat a: https://doi.org/10.1016/j.csbj.2021.10.019
It is part of: Computational And Structural Biotechnology Journal, 2021, vol. 19, p. 5800-5810
URI: http://hdl.handle.net/2445/184242
Related resource: https://doi.org/10.1016/j.csbj.2021.10.019
ISSN: 2001-0370
Appears in Collections:Articles publicats en revistes (Genètica, Microbiologia i Estadística)

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