background prostate cancer is a serious genetic disease known as the first widespread cancer in men, yet the molecular changes required for the cancer progression is not fully understood. availability of high-throughput gene expression data has led to the development of various computational methods for the identification of critical genes involved in the cancer. methods in this paper, we show ...

an important step in considering of gene expression data is obtained groups of genes that have similarity patterns. biclustering methods was recently introduced for discovering subsets of genes that have coherent values across a subset of conditions. the las algorithm relies on a heuristic randomized search to find biclusters. in this paper, we introduce biclustering las algorithm and then appl...

the aim of this study was to propose a method for improving the power of recognition and classification of thromboembolic syndrome based on the analysis of ‎ gene expression data using artificial neural networks. the studied method was performed on a dataset which contained data about 117 patients admitted to a hospital in durham in 2009. of all the studied patients, 66 patients were suffering ...

background: today, despite the many advances in early detection of diseases, cancer patients have a poor prognosis and the survival rates in them are low. recently, microarray technologies have been used for gathering thousands data about the gene expression level of cancer cells. these types of data are the main indicators in survival prediction of cancer. this study highlights the improvement...

we can reach by dna microarray gene expression to such wealth of information with thousands of variables (genes). analysis of this information can show genetic reasons of disease and tumor differences. in this study we try to reduce high-dimensional data by statistical method to select valuable genes with high impact as biomarkers and then classify ovarian tumor based on gene expression data of...