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Updated: Nov 1, 2025

JUMPn: A Streamlined Application for Protein Co-Expression Clustering and Network Analysis in Proteomics
Published on: October 19, 2021
Dark-cutting beef: A brief review and an integromics meta-analysis at the proteome level to decipher the underlying
Mohammed Gagaoua1, Robyn D Warner2, Peter Purslow3
1Food Quality and Sensory Science Department, Teagasc Food Research Centre, Ashtown, Dublin 15, Ireland.
Abstract:
Comprehensive characterization of the post-mortem muscle proteome defines a fundamental goal in meat proteomics. During the last decade, proteomics tools have been applied in the field of foodomics to help decipher factors underpinning meat quality variations and to enlighten us, through data-driven methods, on the underlying mechanisms leading to meat quality defects such as dark-cutting meat known also as dark, firm and dry (DFD) meat. In cattle, several proteomics studies have focused on the extent to which changes in the post-mortem muscle proteome relate to dark-cutting beef development. The present data-mining study firstly reviews proteomics studies which investigated dark-cutting beef, and secondly, gathers the protein biomarkers that differ between dark-cutting versus beef with normal-pH in a unique repertoire. A list of 130 proteins from eight eligible studies was curated and mined through bioinformatics for Gene Ontology annotations, molecular pathways enrichments, secretome analysis and biological pathways comparisons to normal beef color from a previous meta-analysis. The major biological pathways underpinning dark-cutting beef at the proteome level have been described and deeply discussed in this integromics study.
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