首页|Nanjing Agricultural University Reports Findings in Machine Learning (Integratio n of transcriptome and machine learning to identify the potential key genes and regulatory networks affecting drip loss in pork)
Nanjing Agricultural University Reports Findings in Machine Learning (Integratio n of transcriptome and machine learning to identify the potential key genes and regulatory networks affecting drip loss in pork)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-New research on Machine Learning is th e subject of a report. According to news reporting originating from Nanjing, Peo ple's Republic of China, by NewsRx correspondents, research stated, "Low level o f drip loss is an important quality characteristic of meat with high economic va lue. However, the key genes and regulatory networks contributing to drip loss in pork remain largely unknown." Our news editors obtained a quote from the research from Nanjing Agricultural Un iversity, "To accurately identify the key genes affecting drip loss in muscles p ostmortem, 12 Duroc ? (Landrace ? Yorkshire) pigs with extremely high (n = 6, H group) and low (n = 6, L group) drip loss at both 24 h and 48 h postmortem were selected for transcriptome sequencing. The analysis of differentially expressed genes (DEGs) and weighted gene co-expression network analysis (WGCNA) were perfo rmed to find the overlapping genes using the transcriptome data, and functional enrichment and protein-protein interaction (PPI) network analysis were conducted using the overlapping genes. Moreover, we used machine learning to identify the key genes and regulatory networks related to drip loss based on the interactive genes of the PPI network. Finally, nine potential key genes (IRS1, ESR1, HSPA6, INSR, SPOP, MSTN, LGALS4, MYLK2, and FRMD4B) mainly associated with the MAPK si gnaling pathway, the insulin signaling pathway, and the calcium signaling pathwa y were identified, and a single-gene set enrichment analysis (GSEA) was performe d to further annotate the functions of these potential key genes. The GSEA resul ts showed that these genes are mainly related to ubiquitin mediated proteolysis and oxidative reactions."
NanjingPeople's Republic of ChinaAsi aCyborgsEmerging TechnologiesGeneticsMachine LearningPeptide HormonesPeptide ProteinsProinsulin
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