What are the Challenges in Using Computational Resources for Cancer Research?
Despite their potential, there are several challenges in using computational resources for cancer research:
Data Integration: Integrating diverse types of data (genomic, transcriptomic, proteomic, clinical) from different sources remains a significant challenge. Data Privacy: Ensuring the privacy and security of sensitive patient data is critical, especially when dealing with large datasets. Computational Complexity: Analyzing high-dimensional cancer data requires substantial computational power and sophisticated algorithms. Interdisciplinary Collaboration: Effective use of computational resources requires collaboration between biologists, clinicians, and computational scientists. Interpretability: Making sense of the results generated by complex computational models can be challenging and requires domain expertise.
