Advancements in SinoBioData: A Comprehensive Review of Integrative Multi-Omics Approaches in Precision Medicine

• Integrative multi-omics approaches significantly enhance the accuracy of disease subtyping and biomarker discovery compared to single-omics analyses. • Deep learning and network-based models are pivotal in managing high-dimensional, heterogeneous omics data, enabling robust predictive modeling. • Addressing data heterogeneity and missingness through advanced imputation and normalization techniques is critical for reliable cross-omics integration. • Successful clinical translation of multi-omics requires standardized protocols and interdisciplinary collaboration to ensure reproducibility and scalability.