MOTIVATION Protein-protein interactions (PPIs), though extremely valuable towards a better understanding of protein functions and cellular processes, do not provide any direct information about the regions/domains within the proteins that mediate the interaction. Most often, it is only a fraction of a protein that directly interacts with its biological partners. Thus, understanding interaction ...

MOTIVATION Protein-protein interaction (PPI) networks are powerful models to represent the pairwise protein interactions of the organisms. Clustering PPI networks can be useful for isolating groups of interacting proteins that participate in the same biological processes or that perform together specific biological functions. Evolutionary orthologies can be inferred this way, as well as functio...

Identification of protein complexes is of great importance in the understanding of cellular organization and functions. Traditional computational protein complex prediction methods mainly rely on the topology of protein-protein interaction (PPI) networks but seldom take biological information of proteins (such as Gene Ontology (GO)) into consideration. Meanwhile, the environment relevant analys...

The increasing availability of protein-protein interaction graphs (PPI) requires new efficient tools capable of extracting valuable biological knowledge from these networks. Among the wide range of clustering algorithms, Girvan and Newman's edge betweenness algorithm showed remarkable performances in discovering clustering structures in several real-world networks. Unfortunately, their algorith...

Protein-protein interaction (PPI) network analysis presents an essential role in understanding the functional relationship among proteins in a living biological system. Despite the success of current approaches for understanding the PPI network, the large fraction of missing and spurious PPIs and a low coverage of complete PPI network are the sources of major concern. In this paper, based on th...

Recent technological advances have yielded protein-protein interaction (PPI) networks across multiple species. To interpret these networks, comparison methods to characterize interactions across species have gained importance. However, the methodologies of most such studies have been limited to the relationships of protein complexes or pathways between different species because methodologies fo...

Understanding the mathematical properties of graphs underling biological systems could give hints on the evolutionary mechanisms behind these structures. In this article we perform a complete statistical analysis over thousands of graphs representing metabolic and proteinprotein interaction (PPI) networks. The focus of the analysis is, apart from the description of the main properties of the gr...

Protein-protein interactions (PPI), in which, two or more proteins associate with each other by various means, are key to understanding all biological processes that occur within as well as between cells. In effect, biological processes are essentially interactions between multiple proteins (Zhang et al., 2011) with PPI networks controlling the flow of information both within and between biolog...

Protein-protein interactions (PPIs) play a vital role in initiating infection in a number of pathogens. Identifying which interactions allow a pathogen to infect its host can help us to understand methods of pathogenesis and provide potential targets for therapeutics. Public resources for studying host-pathogen systems, in particular PPIs, are scarce. To facilitate the study of host-pathogen PP...