Integration of epigenomic and genomic data to predict residual feed intake and the feed conversion ratio in dairy sheep via machine learning algorithms
The results provide new insights into the biological mechanisms associated with FE and the control of these processes through epigenetic mechanisms. Additionally, the potential use of epigenetic information as a biomarker for the prediction of FE can be suggested based on the obtained results.
Authors
- Cristina Esteban‐Blanco (ORCID: https://orcid.org/0000-0002-2425-000X)
- Héctor Marina (ORCID: https://orcid.org/0000-0001-9226-2902)
- R. Pelayo (ORCID: https://orcid.org/0000-0002-9827-1292)
- Pablo Augusto de Souza Fonseca (ORCID: https://orcid.org/0000-0002-6917-7475)
- Beatriz Gutiérrez‐Gil (ORCID: https://orcid.org/0000-0001-7990-5723)
- Aroa Suárez‐Vega
- Juan-José Arranz
Institutions
- Universidad de León (ES)
Publication Details
- Journal
- BMC Genomics
- Published
- 2025-03-31
- DOI
- https://doi.org/10.1186/s12864-025-11520-1
- Citations
- 2
- Primary Topic
- Genetic and phenotypic traits in livestock
- Type
- article
- Field-Weighted Citation Impact
- 3.63
Funders
- Ministerio de Ciencia, Innovación y Universidades
- European Commission