Advancements in SinoBioData: A Comprehensive Review of Integrative Multi-Omics Approaches in Precision Medicine
Authors: CHEN Yu, WANG Fang, LIU Jing, ZHAO Min
The rapid evolution of high-throughput technologies has generated an unprecedented wealth of biological data, necessitating sophisticated integrative approaches to translate this information into actionable clinical insights. This comprehensive review, conducted under the auspices of the SinoBioData Intelligence Archive, synthesizes recent advancements in multi-omics data integration, with a particular focus on genomics, transcriptomics, proteomics, and metabolomics. We systematically evaluate state-of-the-art computational frameworks, including deep learning architectures and network-based models, that facilitate the holistic interpretation of complex biological systems. Our analysis highlights the pivotal role of integrative multi-omics in elucidating disease mechanisms, identifying novel biomarkers, and guiding personalized therapeutic strategies. Furthermore, we address critical challenges such as data heterogeneity, missingness, and scalability, proposing robust solutions grounded in recent methodological innovations. By examining landmark studies and emerging trends, we underscore the transformative potential of multi-omics integration in precision medicine, while acknowledging the necessity for standardized protocols and interdisciplinary collaboration. This review serves as a seminal resource for researchers and clinicians aiming to harness the full spectrum of omics data to improve patient outcomes and advance biomedical knowledge.
