Cargando…
Aggregation of Omic Data and Secretome Prediction Enable the Discovery of Candidate Plasma Biomarkers for Beef Tenderness
Beef quality is a complex phenotype that can be evaluated only after animal slaughtering. Previous research has investigated the potential of genetic markers or muscle-derived proteins to assess beef tenderness. Thus, the use of low-invasive biomarkers in living animals is an issue for the beef sect...
Autores principales: | Boudon, Sabrina, Henry-Berger, Joelle, Cassar-Malek, Isabelle |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2020
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7013622/ https://www.ncbi.nlm.nih.gov/pubmed/31963926 http://dx.doi.org/10.3390/ijms21020664 |
Ejemplares similares
-
Expression Marker-Based Strategy to Improve Beef Quality
por: Cassar-Malek, Isabelle, et al.
Publicado: (2016) -
A network-based approach for predicting Hsp27 knock-out targets in mouse skeletal muscles
por: Kammoun, Malek, et al.
Publicado: (2013) -
The GENOTEND chip: a new tool to analyse gene expression in muscles of beef cattle for beef quality prediction
por: Hocquette, Jean-Francois, et al.
Publicado: (2012) -
United States beef quality as chronicled by the National Beef Quality Audits, Beef Consumer Satisfaction Projects, and National Beef Tenderness Surveys — A review
por: Gonzalez, John Michael, et al.
Publicado: (2018) -
Cluster analysis application identifies muscle characteristics of importance for beef tenderness
por: Chriki, Sghaier, et al.
Publicado: (2012)