ArticleG3 (Bethesda, Md.)2019
A Benchmarking Between Deep Learning, Support Vector Machine and Bayesian Threshold Best Linear Unbiased Prediction for Predicting Ordinal Traits in Plant Breeding.
Article in G3 (Bethesda, Md.), 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 61 papers.
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Who cites it
61 citing papers in PubMed.
- 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
- Feed-forward neural networks for genomic selection: insights into varying levels of dominance heritability.BMC genomics · 2026Article
- Machine learning for genomic prediction of growth traits in aquaculture: a case study of the Australasian snapper (Chrysophrys auratus).BMC bioinformatics · 2025Article
- Bayesian divergence-based approach for genomic multitrait ordinal selection.G3 (Bethesda, Md.) · 2025Article
- Comparing artificial and convolutional neural networks with traditional models for Genomic prediction in wheat.Molecular breeding : new strategies in plant improvement · 2025Article
- Genomic prediction with kinship-based multiple kernel learning produces hypothesis on the underlying inheritance mechanisms of phenotypic traits.Genome biology · 2025Article
- Genomic prediction with NetGP based on gene network and multi-omics data in plants.Plant biotechnology journal · 2025Article
- Integration of machine learning and genome-wide association study to explore the genomic prediction accuracy of agronomic trait in oats (Avena sativa L.).The plant genome · 2025Article
- Big data and artificial intelligence-aided crop breeding: Progress and prospects.Journal of integrative plant biology · 2025Review
- Genomic Landscape and Prediction of Udder Traits in Saanen Dairy Goats.Animals : an open access journal from MDPI · 2025Article
- Deep learning for genomic selection of aquatic animals.Marine life science & technology · 2024Review
- Machine Learning for the Genomic Prediction of Growth Traits in a Composite Beef Cattle Population.Animals : an open access journal from MDPI · 2024Article
- Evaluation of deep learning for predicting rice traits using structural and single-nucleotide genomic variants.Plant methods · 2024Article
- Improving the accuracy of genomic prediction in dairy cattle using the biologically annotated neural networks framework.Journal of animal science and biotechnology · 2024Article
- Benchmarking machine learning and parametric methods for genomic prediction of feed efficiency-related traits in Nellore cattle.Scientific reports · 2024Article
- A comparative study of 11 non-linear regression models highlighting autoencoder, DBN, and SVR, enhanced by SHAP importance analysis in soybean branching prediction.Scientific reports · 2024Article
- Article
- Multiomics Research: Principles and Challenges in Integrated Analysis.Biodesign research · 2024Review
- Enhancing genomic prediction with Stacking Ensemble Learning in Arabica Coffee.Frontiers in plant science · 2024Article
- Genetic Parameter and Hyper-Parameter Estimation Underlie Nitrogen Use Efficiency in Bread Wheat.International journal of molecular sciences · 2023Article
1 more citing papers are in PubMed but not listed here.
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Authors and funding
8 authors.
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Abstract
Genomic selection is revolutionizing plant breeding. However, still lacking are better statistical models for ordinal phenotypes to improve the accuracy of the selection of candidate genotypes. For this reason, in this paper we explore the genomic based prediction performance of two popular machine learning methods: the Multi Layer Perceptron (MLP) and support vector machine (SVM) methods
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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.