A Machine Learning Method to Identify Genetic Variants Potentially Associated With Alzheimer’s Disease

A Machine Learning Method to Identify Genetic Variants Potentially Associated With Alzheimer’s Disease

There is hope that genomic information will assist prediction, treatment, and understanding of Alzheimer’s disease (AD). Here, using exome data from ∼10,000 individuals, we explore machine learning neural network (NN) methods to estimate the impact of SNPs (i.e., genetic variants) on AD risk. We dev...

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Bibliographic Details
Main Authors: Bradley Monk, Andrei Rajkovic, Semar Petrus, Aleks Rajkovic, Terry Gaasterland, Roberto Malinow
Format: Article
Language:English
Published: Frontiers Media S.A. 2021-06-01
Series:Frontiers in Genetics
Subjects:
machine learning
neural network
Alzheimer’s
disease
polygenic
Online Access:https://www.frontiersin.org/articles/10.3389/fgene.2021.647436/full

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https://www.frontiersin.org/articles/10.3389/fgene.2021.647436/full

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