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Article

Use of support vector machines for disease risk prediction in genome-wide association studies: concerns and opportunities.

Human mutation - 1 Dec 2012

Mittag Florian, Büchel Finja, Saad Mohamad, Jahn Andreas, Schulte Claudia, Bochdanovits Zoltan, Simón-Sánchez Javier, Nalls Mike A, Keller Margaux, Hernandez Dena G, Gibbs J Raphael, Lesage Suzanne, Brice Alexis, Heutink Peter, Martinez Maria, Wood Nicholas W, Hardy John, Singleton Andrew B, Zell Andreas, Gasser Thomas, Sharma Manu

Abstract excerpt

The success of genome-wide association studies (GWAS) in deciphering the genetic architecture of complex diseases has fueled the expectations whether the individual risk can also be quantified based on the genetic architecture. So far, disease risk prediction based on top-validated single-nucleotide polymorphisms (SNPs) showed little predictive value. Here, we applied a support vector machine (SVM) to Parkinson...

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Identifiers

PMID: 22777693
DOI: 10.1002/humu.22161
PMCID: PMC5968822

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PubMed metadata and Literature Corpus relationships. Corpus snapshot updated 6 Sept 2026. Manifest publication-graph-cohort-2026-09-06.1.

Source receipt: pubmed, retrieved 6 Sept 2026.

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