ReviewGenetics2013
Whole-genome regression and prediction methods applied to plant and animal breeding.
Review in Genetics, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 441 papers, 1 of them a synthesis that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
441 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Machine learning for multi-omics data integration in crop improvement: a systematic review.BMC bioinformatics · 2026Pooled it
- Predictive evolutionary genomics: principles, validation, and practice.The New phytologist · 2026Review
- Genomic prediction of agronomic traits in a switchgrass (Panicum virgatum L.) half-sib progeny panel evaluated across multiple environments.The plant genome · 2026Article
- Genetic insights into bacterial wilt resistance using genomic prediction and association mapping in blueberry.The plant genome · 2026Article
- The Role of Prior-Induced Regularization in Accuracy and Stability of Genomic Prediction Across Unimodal and Multimodal Models.Plants (Basel, Switzerland) · 2026Article
- Prioritization of deleterious mutations informs genomic prediction and increases the rate of gain in common bean (Phaseolus vulgaris L.), a simulation study.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2026Article
- Local Enrichment of Multi-SNP Markers Improves Genomic Prediction from Low-Density Genotyping in Pacific White Shrimp.International journal of molecular sciences · 2026Article
- OptimGS: a dual integrative genomic prediction framework for improving cold stress tolerance in wheat.Briefings in bioinformatics · 2026Article
- Conserved leaf-root metabolomic network asymmetry underpins divergent drought strategies.The Plant cell · 2026Article
- Genomic prediction of wild-derived powdery mildew resistance for strawberry (Fragaria × ananassa) pre-breeding.Heredity · 2026Article
- Inference of fitness landscapes with heterogeneous patterns of epistasis across sites.bioRxiv : the preprint server for biology · 2026Article
- Harnessing artificial intelligence in plant breeding: innovations in digital phenotyping and breeding methodologies.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2026Review
- BAGE: a Bayesian framework for age prediction based on PBMC gene expression data.BMC bioinformatics · 2026Article
- Bridging tradition and innovation: a review of computer simulations in plant breeding.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2026Review
- A benchmarking of genomic selection models for predicting grain-yield related traits using haplotype-based and genome-wide association study-based markers in rice.The plant genome · 2026Article
- Proximal regularization of deep residual neural networks applied to high-dimensional genomic data.Briefings in bioinformatics · 2026Article
- Article
- Impact of scale parameter for marker variance prior in some Bayesian whole-genome regression methods.Mammalian genome : official journal of the International Mammalian Genome Society · 2026Article
- From pixels to breeding values: genetic analysis of detection and movement traits in laying hens using automated tracking data of ArUco-marked birds.Genetics, selection, evolution : GSE · 2026Article
- Feed-forward neural networks for genomic selection: insights into varying levels of dominance heritability.BMC genomics · 2026Article
381 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
Abstract
Genomic-enabled prediction is becoming increasingly important in animal and plant breeding and is also receiving attention in human genetics. Deriving accurate predictions of complex traits requires implementing whole-genome regression (WGR) models where phenotypes are regressed on thousands of markers concurrently. Methods exist that allow implementing these large-p with small-n regressions, and genome-enabled selection (GS) is being implemented in several plant and animal breeding programs. The list of available methods is long, and the relationships between them have not been fully addressed. In this article we provide an overview of available methods for implementing parametric WGR models, discuss selected topics that emerge in applications, and present a general discussion of lessons learned from simulation and empirical data analysis in the last decade.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.