Pathway analysis is often the first choice for studying the mechanisms underlying a
phenotype. However, conventional methods for pathway analysis do not take into account …

Omics mainly includes genomics, epigenomics, transcriptomics, proteomics and
metabolomics. The rapid development of omics technology has opened up new ways to …

To analyze gene expression data with sophisticated grouping structures and to extract
hidden patterns from such data, feature selection is of critical importance. It is well known …

PathfindR is a tool for pathway enrichment analysis utilizing active subnetworks. It identifies
gene sets that form active subnetworks in a protein-protein interaction network using a list of …

With the explosion of high-throughput data, effective integrative analyses are needed to
decipher the knowledge accumulated in biological databases. Existing meta-analysis …

Next-generation sequencing approaches and genome-wide studies have become essential
for characterizing the mechanisms of human diseases. Consequently, many researchers …

With the progression of bioinformatics, applications of GE profiles on cancer diagnosis along
with classification have become an intriguing subject in the bioinformatics field. It holds …

To understand the underlying biological mechanisms of gene expression data, it is important
to discover the groups of genes that have similar expression patterns under certain subsets …

Lung cancer is defined as an uncontrolled cell growing in the tissues of lung, which is also
said to be lung tumor. The lung cancer is curable in the starting stage, but identifying the …

Gene Sub-Network-based Feature Selection (GSNFS) is a method capable of handling case-
control and multiclass studies for gene sub-network biomarker identification by an integrated …