Multi-omics integration combines data from genomics, transcriptomics, proteomics, metabolomics, and epigenomics to provide a comprehensive understanding of biological systems. This holistic approach allows researchers to analyze how genes, proteins, metabolites, and molecular pathways interact to influence health and disease. By integrating diverse datasets, multi-omics reveals complex molecular signatures that single-omics methods cannot capture, enabling more accurate disease classification, biomarker discovery, and therapeutic targeting. In precision medicine, multi-omics helps identify patient-specific disease mechanisms, predict treatment responses, and uncover new drug targets. Advanced computational tools and artificial intelligence play a crucial role in interpreting these large datasets, transforming raw biological information into clinically actionable insights.
| 2-5 Days | Initial Quality & Plagiarism Check |
| 15 Days |
Peer Review Feedback |
| 85% | Acceptance Rate (after peer review) |
| 30-45 Days | Total article processing time |