Meat quality is very important for consumers, processors, and producers. The traditional methods for assessing meat quality are subjective and time-consuming, and they do not provide a comprehensive understanding of the factors that affect meat quality. Proteomics, a high-throughput technology for the analysis of entire proteins, has emerged as a powerful tool for investigating the molecular mechanisms underlying the conversion of muscle into meat, meat quality variability, and the discovery of biomarkers. However, the large amount of data generated by meat research proteomics experiments in the last two decades can be overwhelming, and the integration of published meat proteomics datasets through data mining approaches and bioinformatics is a promising way to expand our scientific knowledge. Furthermore, mining such data in their biological context may allow the extraction of novel and more robust biomarkers of meat quality traits. Data reuse is a leading, active, and evolving field suggested and very recently applied in the meat research field to rediscover and reshape the public proteomics data for a better understanding of the unknowns related to meat quality determination and refinement of the list of biomarkers so far proposed. In this talk, the application of integrated data mining and curation approaches to improve our understanding of the molecular basis of meat quality will be presented. The focus will be on important meat quality traits and their defects such as tenderness, color and post-mortem processing treatments (e.g. electrical stimulation). The most updated databases, patterns, knowledge and relationships between different factors and meat quality gained thanks to the integromics studies will be presented. Overall, integrated data mining and proteomics studies curation allowed for providing a comprehensive view of the biochemical mechanisms and molecular signatures underlying meat quality, which all together allowed better insights of their affecting factors. These novel approaches further allowed proposing robust biomarkers for the development of more accurate and efficient methods/tools for assessing meat quality. Integrated data mining and curation of proteomics studies will have important implications for the meat industry, as they will provide new insights into the factors that affect meat quality.