Identification of disease-associated loci using machine learning for genotype and network data integration

MOTIVATION: Integration of different omics data could markedly help to identify biological signatures, understand the missing heritability of complex diseases and ultimately achieve personalized medicine. Standard regression models used in Genome-Wide Association Studies (GWAS) identify loci with a...

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Detalles Bibliográficos
Autores principales: Leal, Luis G, David, Alessia, Jarvelin, Marjo-Riita, Sebert, Sylvain, Männikkö, Minna, Karhunen, Ville, Seaby, Eleanor, Hoggart, Clive, Sternberg, Michael J E
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2019
Materias:
Original Papers
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6954643/
https://www.ncbi.nlm.nih.gov/pubmed/31070705
http://dx.doi.org/10.1093/bioinformatics/btz310

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6954643/
https://www.ncbi.nlm.nih.gov/pubmed/31070705
http://dx.doi.org/10.1093/bioinformatics/btz310

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