Multi-omics datasets refer to datasets that encompass multiple types of biological information, such as genomics, transcriptomics, proteomics, metabolomics, and epigenomics data. By integrating these different types of omics data, researchers can gain a more comprehensive understanding of complex biological systems and processes. This holistic approach allows for a more in-depth analysis of gene expression, protein interactions, metabolic pathways, and other aspects of cellular function. Multi-omics datasets have the potential to uncover novel insights into disease mechanisms, drug responses, and other important biological phenomena.