To study complex biological processes holistically, it is imperative to take an integrative
approach that combines multi-omics data to highlight the interrelationships of the involved …

Recently, feature selection and dimensionality reduction have become fundamental tools for
many data mining tasks, especially for processing high-dimensional data such as gene …

For more than a decade, numerous studies have suggested that the c-Myc oncogenic
protein is likely to broadly influence the composition of the transcriptome. However, the …

Aberrant epidermal growth factor receptor (EGFR) signaling is common in cancer. Increased
expression of wild type and mutant EGFR is a widespread feature of diverse types of cancer …

Since their discovery in the late 1970s, protein kinase C (PKC) isozymes represent one of
the most extensively studied signaling kinases. PKCs signal through multiple pathways and …

Glioblastoma (GBM) is a highly lethal brain tumour presenting as one of two subtypes with
distinct clinical histories and molecular profiles. The primary GBM subtype presents acutely …

Cluster ensembles have been shown to be better than any standard clustering algorithm at
improving accuracy and robustness across different data collections. This meta-learning …

Background The use of clustering methods for the discovery of cancer subtypes has drawn a
great deal of attention in the scientific community. While bioinformaticians have proposed …

Glioblastoma multiforme (GBM) is the most common and lethal primary brain tumor in adults.
We combined neuroimaging and DNA microarray analysis to create a multidimensional map …

Highlights•PDI is an important oxidase, reductase, isomerase and molecular
chaperone.•PDI expression is up-regulated in select types of cancers.•Silencing PDI results …