Abstract
Integrating transcriptomics with other omics data, such as genomics, proteomics, and metabolomics, offers a comprehensive approach to understanding complex diseases. By combining data from multiple layers of biological information, researchers can gain deeper insights into disease mechanisms, identify biomarkers, and discover new therapeutic targets. This article reviews the methods and tools used for integrating transcriptomics with other omics, highlights their applications in disease research, and discusses the challenges and future directions in multi-omics integration
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