Despite its advantages, network segmentation comes with several challenges:
Data Complexity: The enormous amount of data generated by high-throughput technologies can be difficult to manage and analyze. Heterogeneity: Cancer is highly heterogeneous, meaning that different patients can have vastly different genetic and molecular profiles. This heterogeneity can complicate the identification of universally applicable network segments. Integration of Multi-Omics Data: Combining data from different omics layers (genomics, proteomics, metabolomics) requires sophisticated computational approaches and can be computationally intensive. Dynamic Nature of Networks: Biological networks are not static; they change over time and in response to various stimuli, adding another layer of complexity to segmentation efforts.
