Bayesian variable selection for the analysis of microarray data with censored outcomes.
about
Predicting the survival time for diffuse large B-cell lymphoma using microarray data.A method for analyzing censored survival phenotype with gene expression data.Bayesian disease classification using copy number data.SignS: a parallelized, open-source, freely available, web-based tool for gene selection and molecular signatures for survival and censored data.Bayesian variable selection in the accelerated failure time model with an application to the surveillance, epidemiology, and end results breast cancer data.An eScience-Bayes strategy for analyzing omics data.High-dimensional variable selection in meta-analysis for censored data.Bayesian ensemble methods for survival prediction in gene expression dataKernel based methods for accelerated failure time model with ultra-high dimensional data.Bayesian variable selection with joint modeling of categorical and survival outcomes: an application to individualizing chemotherapy treatment in advanced colorectal cancerSemiparametric prognosis models in genomic studies.Ranking prognosis markers in cancer genomic studies.Identification and quantification of metabolites in (1)H NMR spectra by Bayesian model selection.An Efficient Stochastic Search for Bayesian Variable Selection with High-Dimensional Correlated PredictorsBayesian Network Model with Application to Smart Power Semiconductor Lifetime Data.Bayesian profiling of molecular signatures to predict event times.Accelerated failure time models for semi-competing risks data in the presence of complex censoring.Joint Bayesian variable and graph selection for regression models with network-structured predictorsExpression quantitative trait loci mapping with multivariate sparse partial least squares regressionHierarchical Bayesian formulations for selecting variables in regression models.A Gene Selection Method for Survival Prediction in Diffuse Large B-Cell Lymphomas Patients using 1D Discrete Wavelet Transform.Survival analysis with high-dimensional covariates: an application in microarray studies.INCORPORATING BIOLOGICAL INFORMATION INTO LINEAR MODELS: A BAYESIAN APPROACH TO THE SELECTION OF PATHWAYS AND GENES.miRNA-target gene regulatory networks: A Bayesian integrative approach to biomarker selection with application to kidney cancer.Towards Clinically More Relevant Dissection of Patient Heterogeneity via Survival based Bayesian Clustering.Variable Selection for Nonparametric Gaussian Process Priors: Models and Computational Strategies.Variable selection for accelerated lifetime models with synthesized estimation techniques.Bayesian Weibull Survival Model for Gene Expression DataBayesian variable selection for parametric survival model with applications to cancer omics data
P2860
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P2860
Bayesian variable selection for the analysis of microarray data with censored outcomes.
description
2006 nî lūn-bûn
@nan
2006 թուականի Յուլիսին հրատարակուած գիտական յօդուած
@hyw
2006 թվականի հուլիսին հրատարակված գիտական հոդված
@hy
2006年の論文
@ja
2006年論文
@yue
2006年論文
@zh-hant
2006年論文
@zh-hk
2006年論文
@zh-mo
2006年論文
@zh-tw
2006年论文
@wuu
name
Bayesian variable selection for the analysis of microarray data with censored outcomes.
@ast
Bayesian variable selection for the analysis of microarray data with censored outcomes.
@en
type
label
Bayesian variable selection for the analysis of microarray data with censored outcomes.
@ast
Bayesian variable selection for the analysis of microarray data with censored outcomes.
@en
prefLabel
Bayesian variable selection for the analysis of microarray data with censored outcomes.
@ast
Bayesian variable selection for the analysis of microarray data with censored outcomes.
@en
P356
P1433
P1476
Bayesian variable selection for the analysis of microarray data with censored outcomes.
@en
P2093
Mahlet G Tadesse
Naijun Sha
P304
P356
10.1093/BIOINFORMATICS/BTL362
P407
P577
2006-07-15T00:00:00Z