An ensemble learning approach jointly modeling main and interaction effects in genetic association studies.
about
Detecting purely epistatic multi-locus interactions by an omnibus permutation test on ensembles of two-locus analyses.Analysis of North American Rheumatoid Arthritis Consortium data using a penalized logistic regression approach.An omnibus permutation test on ensembles of two-locus analyses can detect pure epistasis and genetic heterogeneity in genome-wide association studies.Identification of interacting genes in genome-wide association studies using a model-based two-stage approachIdentification of multiple gene-gene interactions for ordinal phenotypes.Detecting gene-gene interactions that underlie human diseases.Efficient simulation of epistatic interactions in case-parent trios.SNP selection in genome-wide and candidate gene studies via penalized logistic regression.Ensemble survival tree models to reveal pairwise interactions of variables with time-to-events outcomes in low-dimensional setting.Detecting gene-gene interactions for complex quantitative traits using generalized fuzzy classification
P2860
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P2860
An ensemble learning approach jointly modeling main and interaction effects in genetic association studies.
description
2008 nî lūn-bûn
@nan
2008年の論文
@ja
2008年論文
@yue
2008年論文
@zh-hant
2008年論文
@zh-hk
2008年論文
@zh-mo
2008年論文
@zh-tw
2008年论文
@wuu
2008年论文
@zh
2008年论文
@zh-cn
name
An ensemble learning approach ...... n genetic association studies.
@ast
An ensemble learning approach ...... n genetic association studies.
@en
type
label
An ensemble learning approach ...... n genetic association studies.
@ast
An ensemble learning approach ...... n genetic association studies.
@en
prefLabel
An ensemble learning approach ...... n genetic association studies.
@ast
An ensemble learning approach ...... n genetic association studies.
@en
P2093
P2860
P356
P1433
P1476
An ensemble learning approach ...... n genetic association studies.
@en
P2093
Man-Yu Wong
Qiuying Sha
Shuanglin Zhang
Zhaogong Zhang
P2860
P304
P356
10.1002/GEPI.20304
P577
2008-05-01T00:00:00Z