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BackgroundNasopharyngeal carcinoma (NPC) is a unique cancer. Refinement of current therapy by discovering potential drugs may be approached by several computational strategies.
MethodsWe collected NPC genes from published microarray data and the literature. The NPC disease network was constructed via a protein‐protein interaction (PPI) network. The Connectivity Map (CMap) was used to predict potential...
Hepatocellular carcinoma (HCC) is a severe liver malignancy with few drug treatment options. In finding an effective treatment for HCC, screening drugs that are already FDA-approved will fast track the clinical trial and drug approval process. Connectivity Map (CMap), a large repository of chemical-induced gene expression profiles, provides the opportunity to analyze drug properties on the basis of...
Unbalanced data, minority classes with few samples, present in many applications. It is difficult to solve the problems of unbalanced data by traditional methods. In this paper, a hybrid algorithm based on random over-sampling, decision tree (DT), particle swarm optimization (PSO) and feature selection is proposed to classify unbalanced data. The proposed algorithm has the ability to select beneficial...
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