Medical Anatomy Commons^™

Accurate Molecular Classification Of Cancer Using Simple Rules., Xiaosheng Wang, Osamu Gotoh

Journal Articles: Genetics, Cell Biology & Anatomy

BACKGROUND: One intractable problem with using microarray data analysis for cancer classification is how to reduce the extremely high-dimensionality gene feature data to remove the effects of noise. Feature selection is often used to address this problem by selecting informative genes from among thousands or tens of thousands of genes. However, most of the existing methods of microarray-based cancer classification utilize too many genes to achieve accurate classification, which often hampers the interpretability of the models. For a better understanding of the classification results, it is desirable to develop simpler rule-based models with as few marker genes as possible.

METHODS: …

Role Of Mammalian Ecdysoneless In Cell Cycle Regulation., Jun Hyun Kim, Channabasavaiah B. Gurumurthy, Mayumi Naramura, Ying Zhang, Andrew T. Dudley, Lynn Doglio, Hamid Band, Vimla Band

Journal Articles: Genetics, Cell Biology & Anatomy

The Ecdysoneless (Ecd) protein is required for cell-autonomous roles in development and oogenesis in Drosophila, but the function of its evolutionarily conserved mammalian orthologs is not clear. To study the cellular function of Ecd in mammalian cells, we generated Ecd(lox/lox) mouse embryonic fibroblast cells from Ecd floxed mouse embryos. Cre-mediated deletion of Ecd in Ecd(lox/lox) mouse embryonic fibroblasts led to a proliferative block due to a delay in G(1)-S cell cycle progression; this defect was reversed by the introduction of human Ecd. Loss of Ecd led to marked down-regulation of E2F target gene expression. Furthermore, Ecd directly bound to Rb …

Microarray-Based Cancer Prediction Using Soft Computing Approach., Xiaosheng Wang, Osamu Gotoh

Journal Articles: Genetics, Cell Biology & Anatomy

One of the difficulties in using gene expression profiles to predict cancer is how to effectively select a few informative genes to construct accurate prediction models from thousands or ten thousands of genes. We screen highly discriminative genes and gene pairs to create simple prediction models involved in single genes or gene pairs on the basis of soft computing approach and rough set theory. Accurate cancerous prediction is obtained when we apply the simple prediction models for four cancerous gene expression datasets: CNS tumor, colon tumor, lung cancer and DLBCL. Some genes closely correlated with the pathogenesis of specific or …