Independent component analysis (ICA) methods have received growing attention as
effective data-mining tools for microarray gene expression data. As a technique of higher …

Motivation: Microarrays are capable of determining the expression levels of thousands of
genes simultaneously. One important application of gene expression data is classification of …

Background Gene microarray technology is an effective tool to investigate the simultaneous
activity of multiple cellular pathways from hundreds to thousands of genes. However …

We develop an approach for the exploratory analysis of gene expression data, based upon
blind source separation techniques. This approach exploits higher-order statistics to identify …

This thesis is concerned with the development of Variational Message Passing (VMP), an
algorithm for automatically performing variational inference in a probabilistic graphical …

We propose a new method for tumor classification from gene expression data, which mainly
contains three steps. Firstly, the original DNA microarray gene expression data are modeled …

Background The wide use of high-throughput DNA microarray technology provide an
increasingly detailed view of human transcriptome from hundreds to thousands of genes …

Disclosed are methods and Systems for applying indepen dent component analysis (ICA)
and other advanced signal processing techniques to automatically identify an optimal …

The work presented in this paper describes an incremental hybrid approach that employs
principal component analysis (PCA) and multiple discriminant analysis (MDA) methods for …

Background Many statistical methods have been proposed to identify disease biomarkers
from gene expression profiles. However, from gene expression profile data alone, statistical …