Furthermore, the effectiveness of using FSW score as a PPI reliability index was demonstrated before. Here we ranked the top 10% of protein interactions in the hNek6 third neighbors network by the FSW score and compared to the Class score. We found that the top 10% of PPIs with the best FSW scores were also enriched with the best Class scores A and B: 15.0% were characterized by Class score A and 9.4% by Class score B, compared to 3.8% and 3.3%, respectively, Soyasaponin-Bbconsidering the total PPIs in the network. IIS annotates nodes and edges using diverse databases and metrics, and offers a variety of filters to build the networks, which can be used depending on the type and amount of data to be analyzed. Though, in general, a few steps may be considered: if working with large datasets or organisms with huge interaction databases, the network size can be reduced by using the Class score or FSW score filters; small datasets, the network can give more information when expanded to second or third neighbors; organisms for which only a few interactions were described, the network can be built by using the ‘‘ortholog relationship’’ option selecting a phylogenetically close model organism;Soyosaponin-Ac transcriptome or proteome datasets, the network can be more coherent and concise by expanding it only to first neighbors and using the ‘‘delete nodes with degree 0 and 1’’ option; metabolome datasets, an expansion to second neighbors may be more interesting, since it will probably allow clusters of metabolites and first neighbors to connect with each other; and drugs datasets, the same as for metabolome datasets. Therefore, from the analyses presented above, IIS comes as a platform to perform an integrative analysis of omics data focused on interaction networks, mainly visualized via web or by Cytoscape software, in a more complete and easy-to-interpret way, in order to give a first overview of all the components, their emergent properties and relations and assist researchers to direc further relevant experiments and take important insights of their data. Cell membranes display a wide variety of shapes, including flat sheets, vesicles and tubules.