Abstract: Big data in biology generally refers to omics data generated by multiple high-throughput screening technologies, encompassing genomics, transcriptomics, proteomics, epigenomics, metabolomics, microbiomics, et al. Essentially, it can be regard as the digital record of multi-layered biological activities derived from genetic information flow, and the responses of life systems to environmental changes. The explosive growth of omics data can be attributed to the rapid advancement and widespread adoption of high-throughput sequencing technologies. Simultaneously, the deep integration and application of techniques from biology, mathematics, and computer science have enhanced the analytical and processing capabilities of biological big data. This integration has brought revolutionary impacts on the exploration, innovation, and clinical applications in modern biomedicine. This paper mainly reviews various omics data that constitute biological big data and their applications, while also anticipating future development trends.