Published online 19 May 2009 Nucleic Acids Research, 2009, Vol. 37, Web Server issue W109–W114 doi:10.1093/nar/gkp402 SNOW, a web-based tool for the statistical analysis of protein–protein interaction networks Pablo Minguez1, Stefan Go¨ tz1,2, David Montaner1, Fatima Al-Shahrour1 and Joaquin Dopazo1,2,3,* 1Department of Bioinformatics and Genomics, Centro de Investigacio´ n Prı´ncipe Felipe (CIPF), 2CIBER de Enfermedades Raras (CIBERER) and 3Functional Genomics Node (INB) at CIPF, Valencia, Spain Received January 21, 2009; Revised April 22, 2009; Accepted May 2, 2009 ABSTRACT Understanding the structure and the dynamics of the complex intercellular network of interactions that contributes to the structure and function of a living cell is one of the main challenges of today’s biology. SNOW inputs a collection of protein (or gene) identifiers and, by using the interactome as scaffold, draws the connections among them, calculates several relevant network parameters and, as a novelty among the rest of tools of its class, it estimates their statistical significance. The parameters calculated for each node are: con- nectivity, betweenness and clustering coefficient. It also calculates the number of components, number of bicomponents and articulation points. An interactive network viewer is also available to explore the resulting network. SNOW is available at http://snow.bioinfo.cipf.es. INTRODUCTION It is widely accepted that most of the biological function- ality of the cell arises from complex interactions between their molecular components that deﬁne operational inter- acting entities (1). Understanding the structure and the dynamics of the complex intercellular network of interac- tions that contribute to the structure and function of a living cell is one of the main challenges of today’s biology (2) and constitutes the objective of systems biology (3). Alterations in the network of protein interactions are of special relevance in many diseases. For example, it has recently been demonstrated that tumorigenesis takes place in a speciﬁc and organized way that encompasses the precise down-regulation of groups of topologically- associated proteins (4). For the last years, there has been an enormous interest in the exploration of the interactome of model organisms such as Saccharomyces cerevisiae (5–7), Drosophila melanogaster (8,9), Caenorhabditis elegans (10) or human (11,12), just to cite a few examples. Thus, for several model organisms, a reasonable and oper- ative description of the interactome is available. Several tools exist for network representation and calculation of network parameters, such as the popular Cytoscape (13) and its plugins (14) and other programs (15), but most of them are stand alone applications [see a recent review in (16)]. Also, several web tools for network analysis and visualization have been reported (see Supplementary Table 1) with functionalities that rank from mere network viewers to more sophisticated programs that perform dif- ferent network parameter calculations (17–22). Tools of this type are enormously useful for the interpretation of genomic experiments. For example, if a number of genes has been found to be activated in a microarray experi- ment, their analysis in the context of the interactome can give clues on their possible role as a protein complex, as a signalling pathway, etc. However, the conclusions extracted from the simple visualization of a network of the calculation of some of its parameters are subjective without the proper statistical support. This feature, the proper statistical analysis of networks, still remains to be addressed by a web tool. Here we introduce Studying Networks in the Omics World (SNOW), a unique tool speciﬁcally designed to oﬀer visualization and analysis of protein–protein interacting (PPI) networks, including their statistical analysis. DESCRIPTION OF THE TOOL Functionality of SNOW Essentially, SNOW takes a list of proteins (or genes) and maps them onto an interactome of reference. This inter- actome can be the human interactome (in two versions, see databases subsection) or any other user-deﬁned interactome. Once the list is mapped, SNOW calculates several relevant network parameters for the proteins in the contexts of the interactome and the minimum connected network (MCN) deﬁned by the proteins. The corresponding tests are performed to assess the signiﬁ- cance of the parameters calculated (see below). *To whom correspondence should be addressed. Tel: +34 963289680; Fax: +34 963289701; Email: jdopazo@cipf.es 2009 The Author(s) This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/ by-nc/2.0/uk/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.