1. Data Volume and Complexity: Omics data is vast and complex, requiring sophisticated computational tools and significant computational power to process and analyze.
2. Interdisciplinary Expertise: Effective integration of omics data in catalysis requires expertise in multiple fields, including biology, chemistry, bioinformatics, and computational modeling.
3. Data Standardization: The lack of standardized formats and protocols for omics data can pose challenges for integration and comparison across different studies and platforms.
4. Interpretation of Results: The biological relevance of findings from omics data integration can sometimes be unclear, requiring further experimental validation.
