https://doi.org/10.7490/f1000research.1116765.1
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Squillario M, Barbieri M, Fiorini S et al. Uncovering Alzheimer's SNP signature with a multi-view machine learning analysis based on SNPs, genes and pathways [version 1; not peer reviewed]. F1000Research 2019, 8:685 (poster) (https://doi.org/10.7490/f1000research.1116765.1)
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Uncovering Alzheimer's SNP signature with a multi-view machine learning analysis based on SNPs, genes and pathways

Margherita Squillario1, Matteo Barbieri, Samuele Fiorini, Federico Tomasi, Annalisa Barla
Author Affiliations
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Published 20 May 2019

Uncovering Alzheimer's SNP signature with a multi-view machine learning analysis based on SNPs, genes and pathways

[version 1; not peer reviewed]

Margherita Squillario1, Matteo Barbieri, Samuele Fiorini, Federico Tomasi, Annalisa Barla
Author Affiliations
1 DIBRIS - University of Genoa, Italy
Presented at
13th International Conference on Alzheimer’s and Parkinson’s Diseases and related neurological disorders (AD/PD) 2017
Abstract
Competing Interests

No competing interests were disclosed

Keywords
Late onset Alzheimer’s Disease, GWAS, 3-fold kernel approach, machine learning, SNPs and genes and pathways signatures, new representation of SNP data, signature validation.
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