Abstract Background Graphical Gaussian models are popular tools for the estimation of
(undirected) gene association networks from microarray data. A key issue when the number …

Background It has been long well known that genes do not act alone; rather groups of genes
act in consort during a biological process. Consequently, the expression levels of genes are …

Protein expression and post-translational modification levels are tightly regulated in
neoplastic cells to maintain cellular processes known as 'cancer hallmarks'. The first Pan …

Reverse engineering of gene regulatory networks (GRNs) is one of the most challenging
tasks in systems biology and bioinformatics. It aims at revealing network topologies and …

Technological advances allow for the measurement of high dimensional data sets with small
sample size. When dealing with such high-dimensional data, the consistency of estimations …

Background As an abstract mapping of the gene regulations in the cell, gene regulatory
network is important to both biological research study and practical applications. The …

Gene regulatory network (GRN) reconstruction is the process of identifying regulatory gene
interactions from experimental data through computational analysis. One of the main …

Reconstruction of a biological system from its experimental time series data is a challenging
task in systems biology. The S-system which consists of a group of nonlinear ordinary …

The correlational structure of a set of variables is often conveniently described by the
pairwise partial correlations as they contain the same information as the Pearson …

The response of US soybean export basis (Gulf and Pacific Northwest) to changes in supply
and demand (domestic and international), transportation costs, logistics conditions, and …