<p>Uncovering the genetic hereditable component of late onset Alzheimer’s disease through the analysis of GWA data.</p>

Margherita Squillario; Federico Tomasi; Veronica Tozzo; Annalisa Barla; Daniela Uberti

doi:10.7490/f1000research.1116498.1

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Squillario M, Tomasi F, Tozzo V et al. Uncovering the genetic hereditable component of late onset Alzheimer’s disease through the analysis of GWA data. [version 1; not peer reviewed]. F1000Research 2019, 8:352 (poster) (https://doi.org/10.7490/f1000research.1116498.1)

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Uncovering the genetic hereditable component of late onset Alzheimer’s disease through the analysis of GWA data.

Margherita Squillario¹, Federico Tomasi, Veronica Tozzo, Annalisa Barla, Daniela Uberti

Published 29 Mar 2019 (https://doi.org/10.7490/f1000research.1116498.1)

Author Affiliations

¹ DIBRIS - University of Genova, Italy

Copyright © 2019 Squillario M et al. This is an open access work distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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Published 29 Mar 2019

Uncovering the genetic hereditable component of late onset Alzheimer’s disease through the analysis of GWA data.
[version 1; not peer reviewed]

Margherita Squillario¹, Federico Tomasi, Veronica Tozzo, Annalisa Barla, Daniela Uberti

Author Affiliations

¹ DIBRIS - University of Genova, Italy

Presented at

14th International Conference on Alzheimer’s and Parkinson’s Diseases and related neurological disorders (AD/PD) 2019

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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