How Does It Impact Data Analysis in Cancer Research?
In cancer research, the curse of dimensionality can affect various aspects, including:
Gene Expression Profiling: Analyzing gene expression data involves thousands of genes, making it challenging to identify which genes are relevant for specific cancer types. Biomarker Discovery: Finding reliable biomarkers for cancer diagnosis or prognosis becomes difficult due to the noise and redundancy in high-dimensional data. Predictive Modeling: Building accurate predictive models for cancer outcomes is challenging as more features can lead to overfitting and poor model performance.
