background: protein-protein interactions do not provide any direct information re­garding the domains within the proteins that mediate the interactions. the majority of proteins are multi domain proteins and the interaction between them is often defined by the pairs of their domains. most of the former studies focus only on interacting do­main pairs. however they do not consider the interaction...

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...

Protein-Protein Interaction (PPI) is a network of protein interconnections which regulates most the biological methods. A sound state biota largely depends on synchronized interactions between molecules, and any aberrant molecules may lead to complications, including cervical leukemia, tuberculosis, other neural disorders. In PPI investigation, plethora computational methods have been developed...

The ample availability and importance of large-scale protein-protein interaction (PPI) data demand a flurry research efforts to understand cells' organization, processes, functioning by analyzing these at the network level. In bioinformatics mining fields, clustering requires lot attraction discover clusters interacting proteins. Clustering proteins in PPI has been an excellent method for disco...

Enhancer of zeste homolog 2 (EZH2) is activated in breast cancer, particularly triple-negative cancer (TNBC), and critical for cell invasion. It interacts with embryonic ectoderm development (EED) maintaining stem cells (CSC) epithelial-mesenchymal transition (EMT) properties, hence promoting CSC metastasis. Because the association EZH2 EED promotes catalytic activity EZH2, inhibiting EED-EZH2 ...

MOTIVATION High-throughput protein interaction data, with ever-increasing volume, are becoming the foundation of many biological discoveries, and thus high-quality protein-protein interaction (PPI) maps are critical for a deeper understanding of cellular processes. However, the unreliability and paucity of current available PPI data are key obstacles to the subsequent quantitative studies. It i...

Osteoarthritis is the most common form of arthritis among elderly adults. Herein, we performed protein-protein interaction (PPI) and miRNA network analysis to evaluate the global correlation between miRNA regulation and the PPI network in human osteoarthritis. Our results showed that desmoplakin (DSP), cystatin A (CSTA), calmodulin 1, tyrosine kinase endothelial, insulin-like growth factor 1 (I...

Determining protein-protein interaction (PPI) in biological systems is of considerable importance, and prediction of PPI has become a popular research area. Although different classifiers have been developed for PPI prediction, no single classifier seems to be able to predict PPI with high confidence. We postulated that by combining individual classifiers the accuracy of PPI prediction could be...

Protein-protein interaction (PPI) is essential for almost all cellular processes and identification of PPI is a crucial task for biomedical researchers. So far, most computational studies of PPI are intended for pair-wise prediction. Theoretically, predicting protein partners for a single protein is likely a simpler problem. Given enough data for a particular protein, the results can be more ac...

We present NetLoc, a novel diffusion Kernel-based Logistic Regression (KLR) algorithm for predicting protein subcellular localisation using four types of protein networks including physical PPI networks, genetic Protein-Protein Interaction (PPI) networks, mixed PPI networks and co-expression networks. NetLoc is applied to yeast protein localisation prediction. The results showed that protein ne...