Aim: We aim to predict metastasis in breast cancer patients with tree-based conventional machine learning algorithms and observe which feature selection methods is more effective related microarray data reducing the number of features. Material Methods: Feature methods, least squares absolute shrinkage (LASSO), Boruta maximum relevance-minimum redundancy (MRMR) statistical preprocessing steps w...

Microarray technology is beneficial in terms of diagnosing various diseases, including cancer. Despite all DNA microarray benefits, the high number genes versus low samples has always been a crucial challenge for this technology. Accordingly, we need new optimization algorithms to select optimal faster disease diagnosis. In article, version binary cat algorithm, named SBCSO, gene selection expr...

Microarray gene expression data is used to understand the actions of thousands genes. Just a few genes out have significant impact in any cancer process. Finding these defective using experimental impractical. To locate relevant genes, computational techniques are required. A method identifying candidate from microarray created. Clustering similar necessary find co-expressed different biologica...