Machine Learning-Based Analysis of Differentially Expressed Genes in the Muscle Transcriptome Between Beef Cattle and Dairy Cattle

• Published in: International journal of molecular sciences Vol. 26; no. 11; p. 5046
• Main Authors: Li, Shuai, Guo, Yaqiang, Huo, Chenxi, Zhu, Lin, Shi, Caixia, Gu, Mingjuan, Zhang, Wenguang
• Format: Journal Article
• Language: English
• Published: Switzerland MDPI AG 23.05.2025; MDPI
• Subjects: Accuracy; Adipocytes; Animals; Apolipoproteins; Artificial intelligence; Beef cattle; Biosynthesis; Biotechnology; Cattle - genetics; Dairy cattle; Datasets; Efficiency; Fatty acids; Feeds; Gene Expression Profiling; Gene Expression Regulation; Gene Regulatory Networks; Genes; Genomics; Kinases; Lipid Metabolism - genetics; Lipids; Lipoproteins; Livestock; Machine Learning; Metabolism; Muscle, Skeletal - metabolism; Ontology; Proteins; Red Meat; Support vector machines; Transcriptome - genetics; SHAP; machine learning; transcriptome; muscle

Muscle is a crucial component of cattle, playing a vital role in determining the final quality of beef. This study aimed to identify candidate genes associated with muscle growth and lipid metabolism in beef and dairy cattle by utilizing the public database of the National Center for Biotechnology I...