Chronic obstructive pulmonary disease (COPD) is a growing cause of morbidity and mortality throughout the world. The purpose of our study was to uncover biomarkers and explore its pathogenic mechanisms at the molecular level. The gene expression profiles of COPD samples and normal controls were downloaded from Gene Expression Omnibus. Matlab was used for data preprocessing and SAM4.0 was applie...

In protein-protein interaction (PPI) networks, functional similarity is often inferred based on the function of directly interacting proteins, or more generally, some notion of interaction network proximity among proteins in a local neighborhood. Prior methods typically measure proximity as the shortest-path distance in the network, but this has only a limited ability to capture fine-grained ne...

PURPOSE The study aimed to explore the anticancer effects of a novel proteasome inhibitor, ixazomib, on colorectal cancer (CRC) using a combined method of microarray and bioinformatics analysis. MATERIALS AND METHODS Cell proliferation was tested by Cell Counting Kit-8 (CCK-8) assay for SW620 cells treated with different concentrations of ixazomib and different treatment times. The microarray...

OBJECTIVES To use a systems biology approach to integrate genotype and protein-protein interaction (PPI) data to identify disease network modules associated with chronic obstructive pulmonary disease (COPD) and to perform traditional pathway analysis. METHODS We utilized a standard gene-set association approach (FORGE) using gene-based association analysis and gene-set definitions from the mo...

A central focus of clinical proteomics for cancer is to identify protein biomarkers with diagnostic and therapeutic application potential. Network-based analyses have been used in computational disease-related gene prioritisation for several years. The Random Walk Ranking (RWR) algorithm has been successfully applied to prioritising disease-related gene candidates by exploiting global network t...

The aim of the present study was to investigate the possible pathogenesis of osteosarcoma using bioinformatics analysis to examine gene‑gene interactions. A total of three datasets associated with osteosarcoma were downloaded from the Gene Expression Omnibus. The differentially expressed genes (DEGs) were identified using the significance analysis of microarrays method, which then were subjecte...

OBJECTIVE Determine the adherence to recommendations of concomitant proton-pump inhibitor (PPI) treatment in regular low-dose of aspirin (LDASA) users, taking factors associated with the probability of receiving a PPI into account. DESIGN Cohort study. SETTING Data were obtained from 120 Dutch primary care centres participating in the Netherlands Information Network of Primary Care (LINH). ...

MOTIVATION Large amounts of biological network data exist for many species. Analogous to sequence comparison, network comparison aims to provide biological insight. Graphlet-based methods are proving to be useful in this respect. Recently some doubt has arisen concerning the applicability of graphlet-based measures to low edge density networks-in particular that the methods are 'unstable'-and f...

Clustering protein-protein interaction (PPI) network data yields groups of proteins that are biochemically involved. Most existing clustering methods treat all the proteins in a PPI network equally. However, analyzing host-pathogen networks requires identification of clusters that represent the interactions between the set of pathogen proteins and the set of host proteins. For studying HIV-huma...

An enduring theme in the literature exploring patient and public involvement (PPI) in research has been the focus on evaluating impact, defined usually in terms of participants’ practical contribution to enhancing research processes. By contrast, there has been less emphasis on the perspectives and experiences of those involved in PPI. Drawing on qualitative data with people involved in the Nat...