Protein similarity network generation software tools | Protein interaction data analysis
Protein similarity networks are graphical representations of sequence, structural and other similarities among proteins for which pairwise all-by-all similarity connections have been calculated. Mapping of biological and other information to network nodes or edges enables hypothesis creation about sequence-structure-function relationships across sets of related proteins.
Facilitates analysis of sequence function space in enzyme families using sequence similarity networks (SSNs). EFI-EST is a web-server that generates SSNs in a predominately automated manner. The software allows users to explore local sequence-function space defined by a user-specified sequence and to generate the SSN for any Pfam or InterPro entry. It can be used to analyze sequence-function space in a functionally diverse enzyme superfamily.
Creates and manages protein similarity networks. Pythoscape provides several options to calculate pairwise similarities for input sequences or structures, applies filters to network edges and defines sets of similar nodes and their associated data as single nodes (termed representative nodes) for compression of network information and output data or formatted files for visualization.
Retrieves unit cells sharing characteristics with data stored into the Protein Data Bank. CRYST offers a web application that permits researchers to submit personal files or manual parameters. Users also have the possibility to add information relative to the number of amino acids instead of the molecular weight.
Allows users to detect many of the family/superfamily relationships. SCPS provides an implementation of the spectral clustering algorithm requiring no background knowledge in programming or in the details of spectral clustering algorithms. It can calculate different cluster quality scores and it can produce publication-quality graphical representations of the clusters obtained.
Generates protein similarity networks to be used with Cytoscape. PANADA allows the user to either automatically search similar sequences or to generate a network with a set of selected proteins. The similarity networks can be used for the visual analysis of similarity relationships among sequences or to assess functional annotation inferred from homology. PANADA complements other more traditional tools such as phylogenetic trees and multiple sequence alignments, making use of the user's visual skills to identify patterns that allow the inference of novel properties. The main advantages consist in the automatic search and annotation of proteins with gene ontology (GO) terms from the database and the ability to choose two different approaches to prune the network topology. This produces networks that only contain edges for those pairwise comparisons that represent the highest similarities above a given threshold.
Gathers composite and component gene families and reduces the risk of outputting a large number of false positives. MosaicFinder is based on the graph theoretic tool of clique separator decomposition. It allows users to identify genomes families directly in the similarity network and to generate few false positives. It is reliable for studying fusion events for phylogenetic research as well as for functional biology.
Furnishes a quantitative measure of support values to the branching processes. SCANNET is able to discover communities in generally weighted complex networks. It leads to the phylogenetic classification for the organisms associated to the protein sequences for protein similarity networks. This tool constructs: similarity matrices, protein similarity networks, adjacency matrices, neighborhood matrices and can characterize the properties of the critical network.