Computational approaches for network-based integrative multi-omics analysis.

Advances in omics technologies allow for holistic studies into biological systems. These studies rely on integrative data analysis techniques to obtain a comprehensive view of the dynamics of cellular processes, and molecular mechanisms. Network-based integrative approaches have revolutionized multi-omics analysis by providing the framework to represent interactions between multiple different omics-layers in a graph, which may faithfully reflect the molecular wiring in a cell.

Whole-genome analysis of strains isolated from persons with cystic fibrosis.

is a commensal of the respiratory tract that is frequently present in cystic fibrosis (CF) patients and may cause infection. Antibiotic resistance is well described for CF strains, and virulence factors have been proposed. The genetic diversity of strains present in the lungs of persons with CF is largely unknown despite the fact that this organism is considered to be a pathogen in this condition.

Taxonomic position, antibiotic resistance and virulence factors of clinical isolates.

The role of species in lung disease remains unclear. The aim of this study was to characterize isolated from persons with cystic fibrosis and from other clinical samples. Whole genome sequences from 101 isolates were determined (81 from patients with cystic fibrosis and 20 from other patients) and analysed.

Taxonomic position, antibiotic resistance and virulence factor production by Stenotrophomonas isolates from patients with cystic fibrosis and other chronic respiratory infections.

Background: The potential pathogenic role of Stenotrophomonas maltophilia in lung disease and in particular in cystic fibrosis is unclear. To develop further understanding of the biology of this taxa, the taxonomic position, antibiotic resistance and virulence factors of S. maltophilia isolates from patients with chronic lung disease were studied.