Cancer data is inherently complex due to several reasons:
1. Genetic Variability: Each cancer type can have numerous genetic mutations. For example, breast cancer alone has multiple subtypes, each with unique genetic profiles. 2. Environmental Factors: External factors like exposure to carcinogens, diet, and lifestyle choices contribute to cancer development, making the data even more multifaceted. 3. Heterogeneity: Tumors are often heterogeneous, containing multiple cell types with different genetic mutations and characteristics. 4. Temporal Changes: Tumors evolve over time, responding to treatments and developing resistance, requiring longitudinal data analysis. 5. Multi-Omics Data: Integrating different types of biological data, such as genomics, transcriptomics, proteomics, and metabolomics, adds another layer of complexity.
