https://www.selleckchem.com/
First, an iterative optimization algorithm learns model parameters on the TCGA breast cancer dataset to investigate the classification performance. Then, we probe the distribution patterns of GLassonet-selected gene sets across the cancer subtypes and compare them to gene sets outputted from the state-of-the-art. More profoundly, we conduct the overall survival analysis on three GLassonet-selected new marker genes, i.e., SOX10, TPX2, and TUBA1C, to investigate their expression changes and assess their prognostic impacts. Finally, we perform the enrichment a
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