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Hepatocyte growth factor (HGF), the ligand for MET, has been shown to rapidly induce phosphorylation of PXN., Stable transfectants of wild-type and PXN mutants in HEK-293 cells were created for further cellular functional analysis.
Molecular and cellular functional analysis using Ingenuity Pathway Analysis (IPA) found these genes to be associated with lipid and carbohydrate metabolism, small molecule biochemistry, cell cycle and gene expression based on a Fisher's Exact Test p-value < 0.01.
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Comprehension of the pathogenetic potential of human parvovirus B19 requires the definition of the complete spectrum of cellular tropism and a functional analysis of the viral genome in infected cells.
Though these methods provide a broad coverage in determining cellular activities, little integrated functional analysis has been performed to date.
We set forth a "reverse" functional analysis approach, whereby cellular functions are reconstructed from the analysis of dynamic envirome data.
We applied an innovative method in which we tested for the effect of groups of genes defined according to cellular function (functional gene group analysis).
Functional analysis of cellular response variability demonstrates that the observed cellular variability affects the core function of signaling networks.
An additional positive aspect of adding process partitions to an analysis is that once a large number of partitions from various cellular functional classes are available, partitioned analysis will also allow detailed examination of the evolutionary dynamics of these classes of genes.
The model studied in this work was implemented in and analysed with CellNetAnalyzer, a comprehensive toolbox for functional analysis of cellular networks [ 14].
Consistently with the preliminary biological indications derived from the most CHKA-comodulated genes, IPA functional analysis, identified as the most perturbed cellular functions those related to cell death and cellular proliferation and movement.
In the post-genomic era, the large-scale, systematic, and functional analysis of all cellular components using transcriptomics, proteomics, and metabolomics, together with bioinformatics for the analysis of the massive amount of data generated by these "omics" methods are the focus of intensive research activities.
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