With the rapid development of high-throughput sequencing technology, omics data that are available as genomics, transcriptomics, proteomics and metabolomics, have been widely used to study the underlying mechanisms of important biological processes. In recent times, multi-omics data integration has attracted extensive attention in the field of medicine and biology, such as conceptual introduction of multi-omics [1–4], multi-omics data processing techniques [5–8], and disease treatment and prevention [5, 9]. Compared with a single omics, multi-omics data can provide more comprehensive and extensive information, thus integrated analysis of multi-omics data can verify and help to complement each other, which can help us identify better biomarkers for high-precision diagnosis, prognosis and predictive treatment.

中文翻译：

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功能基因组学简报专区社论：综合多组学数据分析

随着高通量测序技术的快速发展，基因组学、转录组学、蛋白质组学和代谢组学等组学数据已被广泛用于研究重要生物过程的潜在机制。近年来，多组学数据集成在医学和生物学领域引起了广泛关注，如多组学概念介绍[1-4]、多组学数据处理技术[5-8]、疾病治疗等。和预防 [5, 9]。与单一组学相比，多组学数据可以提供更全面、更广泛的信息，因此多组学数据的综合分析可以验证并帮助相互补充，可以帮助我们识别出更好的生物标志物，用于高精度诊断、预后和诊断。预测性治疗。