Predictive modeling of schizophrenia from genomic data: Comparison of polygenic risk score with kernel support vector machines approach

A major controversy in psychiatric genetics is whether nonadditive genetic interaction effects contribute to the risk of highly polygenic disorders. We applied a support vector machines (SVMs) approach, which is capable of building linear and nonlinear models using kernel methods, to classify cases...

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Detalles Bibliográficos
Autores principales: Vivian‐Griffiths, Timothy, Baker, Emily, Schmidt, Karl M., Bracher‐Smith, Matthew, Walters, James, Artemiou, Andreas, Holmans, Peter, O'Donovan, Michael C., Owen, Michael J., Pocklington, Andrew, Escott‐Price, Valentina
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley & Sons, Inc. 2018
Materias:
Research Articles
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6492016/
https://www.ncbi.nlm.nih.gov/pubmed/30516002
http://dx.doi.org/10.1002/ajmg.b.32705

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6492016/
https://www.ncbi.nlm.nih.gov/pubmed/30516002
http://dx.doi.org/10.1002/ajmg.b.32705

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