CSDA
2011
12 years 8 months ago
2011
Multivariate outlier identification requires the choice of reliable cut-off points for the robust distances that measure the discrepancy from the fit provided by high-breakdown...
GCB
2010
Springer
13 years 3 months ago
2010
Springer
Abstract: The search for local RNA secondary structures and the annotation of unusually stable folding regions in genomic sequences are two well motivated bioinformatic problems. I...
BMCBI
2005
13 years 5 months ago
2005
Background: In the analysis of microarray data one generally produces a vector of p-values that for each gene give the likelihood of obtaining equally strong evidence of change by...
BMCBI
2006
13 years 5 months ago
2006
In this short article, we discuss a simple method for assessing sample size requirements in microarray experiments. Our method starts with the output from a permutation-based anal...
BMCBI
2006
13 years 5 months ago
2006
Background: Nonlinear regression, like linear regression, assumes that the scatter of data around the ideal curve follows a Gaussian or normal distribution. This assumption leads ...
CSSC
2008
13 years 5 months ago
2008
The interest in inference in the wavelet domain remains vibrant area of statistical research because of needs of scientific community to process and explore massive data sets. Prim...
BMCBI
2008
13 years 5 months ago
2008
Background: In microarray experiments the numbers of replicates are often limited due to factors such as cost, availability of sample or poor hybridization. There are currently fe...
BMCBI
2008
13 years 5 months ago
2008
Background: Microarray technology provides an efficient means for globally exploring physiological processes governed by the coordinated expression of multiple genes. However, ide...
BMCBI
2007
13 years 5 months ago
2007
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...
BMCBI
2008
13 years 5 months ago
2008
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 ...