A Ranking Approach for Probe Selection and Classification of Microarray Data with Artificial Neural Networks.

Acute leukemia classification into its myeloid and lymphoblastic subtypes is usually accomplished according to the morphology of the tumor. Nevertheless, the subtypes may have similar histopathological appearance, making screening procedures difficult. In addition, approximately one-third of acute myeloid leukemias are characterized by aberrant cytoplasmic localization of nucleophosmin (NPMc(+)), where the majority has a normal karyotype.

Sequential selection of variables using short permutation procedures and multiple adjustments: An application to genomic data.

This work proposes a sequential methodology for selecting variables in classification problems in which the number of predictors is much larger than the sample size. The methodology includes a Monte Carlo permutation procedure that conditionally tests the null hypothesis of no association among the outcomes and the available predictors. In order to improve computing aspects, we propose a new parametric distribution, the Truncated and Zero Inflated Gumbel Distribution.

SET domain-containing Protein 4 (SETD4) is a Newly Identified Cytosolic and Nuclear Lysine Methyltransferase involved in Breast Cancer Cell Proliferation.

Cancer is comprised of a multitude of epigenetic abnormalities, including the global loss and regional gain of DNA methylation as well as alterations in histone methylation. Here, we characterize a new methyltransferase, SET domain-containing protein 4 (SETD4), which is involved in breast carcinogenesis. Quantitative real-time PCR (qPCR) showed elevated expression levels of SETD4 in several breast cancer cell lines.