Joint high-dimensional Bayesian variable and covariance selection with an application to eQTL analysis.
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HDTD: analyzing multi-tissue gene expression data.Statistical Methods in Integrative GenomicsModelling survival data to account for model uncertainty: a single model or model averaging?Inferring network structure in non-normal and mixed discrete-continuous genomic data.Multiple SNP Set Analysis for Genome-Wide Association Studies Through Bayesian Latent Variable Selection.Multiple-response regression analysis links magnetic resonance imaging features to de-regulated protein expression and pathway activity in lower grade glioma.Semiparametric Bayes conditional graphical models for imaging genetics applications.High-dimensional regression analysis links magnetic resonance imaging features and protein expression and signaling pathway alterations in breast invasive carcinoma.
P2860
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P2860
Joint high-dimensional Bayesian variable and covariance selection with an application to eQTL analysis.
description
2013 nî lūn-bûn
@nan
2013年の論文
@ja
2013年学术文章
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2013年学术文章
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2013年学术文章
@zh-hans
2013年学术文章
@zh-my
2013年学术文章
@zh-sg
2013年學術文章
@yue
2013年學術文章
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2013年學術文章
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name
Joint high-dimensional Bayesia ...... application to eQTL analysis.
@en
Joint high-dimensional Bayesia ...... application to eQTL analysis.
@nl
type
label
Joint high-dimensional Bayesia ...... application to eQTL analysis.
@en
Joint high-dimensional Bayesia ...... application to eQTL analysis.
@nl
prefLabel
Joint high-dimensional Bayesia ...... application to eQTL analysis.
@en
Joint high-dimensional Bayesia ...... application to eQTL analysis.
@nl
P2860
P356
P1433
P1476
Joint high-dimensional Bayesia ...... application to eQTL analysis.
@en
P2093
Anindya Bhadra
Bani K Mallick
P2860
P304
P356
10.1111/BIOM.12021
P407
P577
2013-04-22T00:00:00Z