Background: In the context of genomic association studies, for which a large number of statistical tests are performed simultaneously, the local False Discovery Rate (lFDR), which...
Background: False discovery rate (FDR) methods play an important role in analyzing highdimensional data. There are two types of FDR, tail area-based FDR and local FDR, as well as ...
Background: Novel strategies are required in order to handle the huge amount of data produced by microarray technologies. To infer gene regulatory networks, the first step is to f...
— Sensor networks (SNETs) for monitoring spatial phenomena has emerged as an area of significant practical interest. We focus on the important problem of detection of distribute...
Background: Thousands of genes in a genomewide data set are tested against some null hypothesis, for detecting differentially expressed genes in microarray experiments. The expect...