Patient and public involvement (PPI) in research involves the active contribution of members of the public in research studies and within research organisations. PPI is important in ensuring the relevance and quality of general health care research. Funders often now request evidence of prior and future planned PPI in health research. The University of Liverpool Clinical Trials Research Centre ...

It is widely believed that comparing discrepancies in the protein-protein interaction (PPI) networks of individuals will become an important tool in understanding and preventing diseases. Currently PPI networks for individuals are not available, but gene expression data is becoming easier to obtain and allows us to represent individuals by a co-integrated gene expression/protein interaction net...

Essentially all biological processes depend on protein-protein interactions (PPIs). Timing of such interactions is crucial for regulatory function. Although circadian (~24-hour) clocks constitute fundamental cellular timing mechanisms regulating important physiological processes, PPI dynamics on this timescale are largely unknown. Here, we identified 109 novel PPIs among circadian clock protein...

The aim of the present study was to identify differentially expressed genes and biological processes associated with periodontitis. In this study, the most significant 200 differentially expressed genes associated with periodontitis were identified using integrated analysis of multiple microarray data in combination with screening for genome‑wide relative significance and genome‑wide global sig...

Background. KDM6A (Lysine (K)-Specific Demethylase 6A) is the driver gene related to esophageal squamous cell carcinoma (ESCC). In order to provide more biological insights into KDM6A, in this paper, we treat PPI (protein-protein interaction) network derived from KDM6A as a conceptual framework and follow it to review its biological function. Method. We constructed a PPI network with Cytoscape ...

We investigated the biological significance of path lengths in 12 protein-protein interaction (PPI) networks. We put forward three predictions, based on the idea that biological complexity influences path lengths. First, at the network level, path lengths are generally longer in PPIs than in random networks. Second, this pattern is more pronounced in more complex organisms. Third, within a PPI ...

Proteins in the same protein complexes should highly interact with each other but rarely interact with the other proteins in protein-protein interaction (PPI) networks. All interaction network weighting schemes have been proposed so far in the literature in order to eliminate the noise inherent in interactome data. Visualization representation of data visually and is an important task in scient...

The aim of this study is to analyze gene expression data to identify key genes and pathways associated with resistance to platinum-based chemotherapy in epithelial ovarian cancer (EOC) and to improve clinical treatment strategies. The gene expression data set was downloaded from Gene Expression Omnibus and included 12 chemotherapy-resistant EOC samples and 16 chemotherapy-sensitive EOC samples....

We propose here a multi-label semi-supervised learning algorithm, PfunBG, to predict protein functions, employing a bi-relational graph (BG) of proteins and function annotations. Different from most, if not all, existing methods that only consider the partially labeled proteinprotein interaction (PPI) network, the BG comprises three components, a PPI network, a function class graph induced from...

As a gynecological oncology, ovarian cancer has high incidence and mortality. To study the mechanisms of ovarian cancer, the present study analyzed the GSE37582 microarray. GSE37582 was downloaded from Gene Expression Omnibus and included data from 74 ovarian cancer cases and 47 healthy controls. The differentially-expressed genes (DEGs) were screened using linear models for microarray data pac...