Simultaneous identification of robust synergistic subnetwork markers for effective cancer prognosis
Accurate prediction of cancer prognosis based on gene expression data is generally difficult, and identifying robust prognostic markers for cancer remains a challenging problem. Recent studies have shown that modular markers, such as pathway markers and subnetwork markers, can provide better snapshots of the underlying biological mechanisms by incorporating additional biological information, thereby leading to more accurate cancer classification.
cancer classification subnetwork marker identification protein-protein interaction network message-passing algorithm