A kernel machine method for detecting effects of interaction between multidimensional variable sets: an imaging genetics application.
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A cautionary note on using secondary phenotypes in neuroimaging genetic studies.The effect of the top 20 Alzheimer disease risk genes on gray-matter density and FDG PET brain metabolism.A Set-Based Mixed Effect Model for Gene-Environment Interaction and Its Application to Neuroimaging Phenotypes.FGWAS: Functional genome wide association analysis.Generalized reduced rank latent factor regression for high dimensional tensor fields, and neuroimaging-genetic applications.
P2860
A kernel machine method for detecting effects of interaction between multidimensional variable sets: an imaging genetics application.
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2015 nî lūn-bûn
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2015 թուականի Յունուարին հրատարակուած գիտական յօդուած
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2015 թվականի հունվարին հրատարակված գիտական հոդված
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2015年の論文
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2015年学术文章
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2015年学术文章
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name
A kernel machine method for de ...... imaging genetics application.
@ast
A kernel machine method for de ...... imaging genetics application.
@en
type
label
A kernel machine method for de ...... imaging genetics application.
@ast
A kernel machine method for de ...... imaging genetics application.
@en
prefLabel
A kernel machine method for de ...... imaging genetics application.
@ast
A kernel machine method for de ...... imaging genetics application.
@en
P2093
P2860
P50
P1433
P1476
A kernel machine method for de ...... imaging genetics application.
@en
P2093
Debashis Ghosh
Elizabeth C Mormino
Jordan W Smoller
Thomas E Nichols
P2860
P304
P356
10.1016/J.NEUROIMAGE.2015.01.029
P407
P577
2015-01-16T00:00:00Z