| no |
title |
author |
magazine |
year |
volume |
issue |
page(s) |
type |
| 1 |
An Integrated Approach to Empirical Bayesian Whole Genome Prediction Modeling
|
Chen, C.
|
|
2015
|
20 |
4 |
p. 491-511
|
article
|
| 2 |
A Semi-parametric Bayesian Approach for Differential Expression Analysis of RNA-seq Data
|
Liu, Fangfang
|
|
2015
|
20 |
4 |
p. 555-576
|
article
|
| 3 |
Detecting Differentially Expressed Genes with RNA-seq Data Using Backward Selection to Account for the Effects of Relevant Covariates
|
Nguyen, Yet
|
|
2015
|
20 |
4 |
p. 577-597
|
article
|
| 4 |
Empirical Bayes Analysis of RNA-seq Data for Detection of Gene Expression Heterosis
|
Niemi, Jarad
|
|
2015
|
20 |
4 |
p. 614-628
|
article
|
| 5 |
Genomic Prediction Models for Count Data
|
Montesinos-López, Osval A.
|
|
2015
|
20 |
4 |
p. 533-554
|
article
|
| 6 |
Guest Editors’ Introduction to the Special Issue on “Statistical Genomics and Transcriptomics in Agriculture”
|
Nettleton, Dan
|
|
2015
|
20 |
4 |
p. 439-441
|
article
|
| 7 |
Hierarchical Modeling and Differential Expression Analysis for RNA-seq Experiments with Inbred and Hybrid Genotypes
|
Lithio, Andrew
|
|
2015
|
20 |
4 |
p. 598-613
|
article
|
| 8 |
Incorporating Genetic Heterogeneity in Whole-Genome Regressions Using Interactions
|
Campos, Gustavo de los
|
|
2015
|
20 |
4 |
p. 467-490
|
article
|
| 9 |
Selection of the Bandwidth Parameter in a Bayesian Kernel Regression Model for Genomic-Enabled Prediction
|
Pérez-Elizalde, Sergio
|
|
2015
|
20 |
4 |
p. 512-532
|
article
|
| 10 |
Statistical and Computational Challenges in Whole Genome Prediction and Genome-Wide Association Analyses for Plant and Animal Breeding
|
Tempelman, Robert J.
|
|
2015
|
20 |
4 |
p. 442-466
|
article
|
Journal description