Network querying software tools | Protein interaction data analysis
Network querying algorithms provide computational means to identify conserved network modules in large-scale biological networks that are similar to known functional modules, such as pathways or molecular complexes. Two main challenges for network querying algorithms are the high computational complexity of detecting potential isomorphism between the query and the target graphs and ensuring the biological significance of the query results.
Provides functions for the import-export of some standard systems biology file formats and a set of algorithms to analyze and reduce the complexity of biological networks. BiNoM provides the user with a complete interface for the analysis of biological networks in Cytoscape environment.
Provides several tools for bioinformatics analysis. Corbi is an R package that contains functions for network querying and alignment, subnetwork extraction, search and biomarker identification. The software includes the network querying method named CNetQ, CNetA, which extended CNetQ to the pairwise network alignment problem with one-to-one mapping and MarkRank, an enhanced biomarker ranking method.
A network alignment and search tool for comparing protein interaction networks across species to identify protein pathways and complexes that have been conserved by evolution. The basic method searches for high-scoring alignments between pairs of protein interaction paths, for which proteins of the first path are paired with putative orthologs occurring in the same order in the second path. This technique discriminates between true- and false-positive interactions and allows for functional annotation of protein interaction pathways based on similarity to the network of another, well-characterized species.
A comprehensive alignment tool for PPI networks, which is inspired by duplication/divergence models that focus on understanding the evolution of protein interactions. MaWISh is based on a mathematical model that extends the concepts of match, mismatch, and gap in sequence alignment to that of match, mismatch, and duplication in network alignment and evaluates the similarity between graph structures through a scoring function that accounts for evolutionary events. By relying on evolutionary models, it facilitates interpretation of resulting alignments in terms of not only conservation but also divergence of modularity in PPI networks. Furthermore, as in the case of sequence alignment, MaWISh allows flexibility in adjusting parameters to quantify underlying evolutionary relationships.
Allows network querying. RESQUE takes a reduction-based approach, where the target network is iteratively reduced based on the so-called node correspondence scores that are computed using a semi-Markov random walk (SMRW) model. It is able to produce good results in network querying techniques, in terms of computational efficiency and querying accuracy. This tool can deal with node insertions and deletions at arbitrary locations.
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