Regularized group regression methods for genomic prediction: Bridge, MCP, SCAD, group bridge, group lasso, sparse group lasso, group MCP and group SCAD.
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PLS-Based and Regularization-Based Methods for the Selection of Relevant Variables in Non-targeted Metabolomics DataXVI(th) QTLMAS: simulated dataset and comparative analysis of submitted results for QTL mapping and genomic evaluation.Iterative sure independence screening EM-Bayesian LASSO algorithm for multi-locus genome-wide association studies.A semi-mechanism approach based on MRI and proteomics for prediction of conversion from mild cognitive impairment to Alzheimer's diseaseAn efficient unified model for genome-wide association studies and genomic selection.Group Spike-and-Slab Lasso Generalized Linear Models for Disease Prediction and Associated Genes Detection by Incorporating Pathway Information.
P2860
Regularized group regression methods for genomic prediction: Bridge, MCP, SCAD, group bridge, group lasso, sparse group lasso, group MCP and group SCAD.
description
2014 nî lūn-bûn
@nan
2014 թուականի Հոկտեմբերին հրատարակուած գիտական յօդուած
@hyw
2014 թվականի հոտեմբերին հրատարակված գիտական հոդված
@hy
2014年の論文
@ja
2014年論文
@yue
2014年論文
@zh-hant
2014年論文
@zh-hk
2014年論文
@zh-mo
2014年論文
@zh-tw
2014年论文
@wuu
name
Regularized group regression m ...... sso, group MCP and group SCAD.
@ast
Regularized group regression m ...... sso, group MCP and group SCAD.
@en
type
label
Regularized group regression m ...... sso, group MCP and group SCAD.
@ast
Regularized group regression m ...... sso, group MCP and group SCAD.
@en
prefLabel
Regularized group regression m ...... sso, group MCP and group SCAD.
@ast
Regularized group regression m ...... sso, group MCP and group SCAD.
@en
P2860
P1433
P1476
Regularized group regression m ...... sso, group MCP and group SCAD.
@en
P2860
P2888
P356
10.1186/1753-6561-8-S5-S7
P433
P577
2014-10-07T00:00:00Z
P5875
P6179
1032730147