Background To construct gene co-expression networks, it is necessary to evaluate the
correlation between different gene expression profiles. However, commonly used correlation …

With the recent advancement of computing technique and data availability in the field of
computational biology, it has been a great opportunity for the scientists to find the …

In diagnosis and classification diseases multiple outcomes, both molecular and
clinical/pathological are routinely gathered on patients. In recent years, many approaches …

Statistical analysis of high-dimensional biological data is the central component of
“personalized medicine” and “translational bioinformatics.” Two major barriers limit the …

Background Identification of gene-phenotype relationships is a fundamental challenge in
human health clinic. Based on the observation that genes causing the same or similar …

Microarray technology enables us to measure the expression of tens of thousands of genes
simultaneously under various experimental conditions. Clustering analysis is one of the …

In life threatening diseases, such as cancer, where the effective diagnosis includes
annotation, early detection, distinction, and prediction, data mining and statistical …

Abstract Motivation: Gaussian graphical models (GGMs) are a popular tool for representing
gene association structures. We propose using estimated partial correlations from these …

Investigators require intuitive tools to rationalize complex datasets generated by
transcriptional profiling experiments. Pathway analysis methods, in which differentially …

Cluster analysis is usually the first step adopted to unveil information from gene expression
microarray data. Besides selecting a clustering algorithm, choosing an appropriate proximity …