# Genomic prediction using machine learning: a comparison of the performance of regularized regression, ensemble, instance-based and deep learning methods on synthetic and empirical data

*PRI Rank #5 · Topics and Trends in Most Cited Genetic and phenotypic traits in livestock Papers, Class of 2026*

*Canonical URL: https://pri.pepkio.com/top-papers/genetic-and-phenotypic-traits-in-livestock/2026/rank-5*

| Field | Value |
| --- | --- |
| Rank | #5 |
| 18m citations | 25 |
| Journal | BMC Genomics |
| Year | 2024 |
| DOI | 10.1186/s12864-023-09933-x |
| Corresponding authors | Vanda M Lourenço |
| Institution | NOVA SST, Portugal |

**Ranking page:** [Topics and Trends in Most Cited Genetic and phenotypic traits in livestock Papers, Class of 2026](https://pri.pepkio.com/top-papers/genetic-and-phenotypic-traits-in-livestock/2026)

**Paper link:** [10.1186/s12864-023-09933-x](https://doi.org/10.1186/s12864-023-09933-x)

## Topics

genomic prediction · genomic selection · molecular markers · regularized regression · ensemble learning · instance-based learning · deep learning · adaptive regularization · group regularization · linear mixed model · breeding value · high dimensional data · computational performance · Predictive accuracy · simulated animal breeding dataset · empirical maize breeding datasets · commercial breeding program · target trait dependence · model complexity · supervised machine learning methods

## Cite this ranking

```
Pepkio Research Index (PRI). Topics and Trends in Most Cited Genetic and phenotypic traits in livestock Papers, Class of 2026. https://pri.pepkio.com/top-papers/genetic-and-phenotypic-traits-in-livestock/2026. Accessed 2026-07-15.

Zheng Su, Tinsley Li, Thematic Shifts in Early-High-Impact Cancer Genomics and Diagnostics Research: A Bibliometric and Semantic Analysis. bioRxiv 2026.07.04.736459; doi: https://doi.org/10.64898/2026.07.04.736459
```