Despite its potential, integrative genomics faces several challenges:
Data heterogeneity: Different types of data have varying formats, quality, and scale, making integration complex. Computational complexity: Integrating large datasets requires significant computational resources and sophisticated algorithms. Interpretation of results: Identifying meaningful patterns and biological significance from integrated data can be challenging. Clinical translation: Applying findings from integrative genomics to clinical practice requires robust validation and regulatory approval.
