This article is part of the supplement: Italian Society of Bioinformatics (BITS): Annual Meeting 2007
The MoVIN server for the analysis of protein interaction networks
1 Department of Biochemical Sciences, “Sapienza” University, Rome, Italy
2 Istituto Pasteur – Fondazione “Cenci Bolognetti”, Rome, Italy
BMC Bioinformatics 2008, 9(Suppl 2):S11 doi:10.1186/1471-2105-9-S2-S11Published: 26 March 2008
Protein-protein interactions are at the basis of most cellular processes and crucial for many bio-technological applications. During the last few years the development of high-throughput technologies has produced several large-scale protein-protein interaction data sets for various organisms. It is important to develop tools for dissecting their content and analyse the information they embed by data-integration and computational methods.
Interactions can be mediated by the presence of specific features, such as motifs, surface patches and domains. The co-occurrence of these features on proteins interacting with the same protein can indicate mutually exclusive interactions and, therefore, can be used for inferring the involvement of the proteins in common biological processes.
We present here a publicly available server that allows the user to investigate protein interaction data in light of other biological information, such as their sequences, presence of specific domains, process and component ontologies. The server can be effectively used to construct a high-confidence set of mutually exclusive interactions by identifying similar features in groups of proteins sharing a common interaction partner. As an example, we describe here the identification of common motifs, function, cellular localization and domains in different datasets of yeast interactions.
The server can be used to analyse user-supplied datasets, it contains pre-processed data for four yeast Protein Protein interaction datasets and the results of their statistical analysis. These show that the presence of common motifs in proteins interacting with the same partner is a valuable source of information, it can be used to investigate the properties of the interacting proteins and provides information that can be effectively integrated with other sources. As more experimental interaction data become available, this tool will become more and more useful to gain a more detailed picture of the interactome.