Biological data such as genomic, transcriptomics, proteomic, metabolomics, or clinical data are used for analyzing the patterns in breast cancer. Early diagnosis and identification are vital in precise therapy for the adverse breast cancer effects. Recent studies have focused on utilizing Deep Learning (DL) algorithms like deep convolutional neural Networks (CNN) architectures for breast cancer classification tasks with high efficiency from gene expression profiles