Local network alignment software tools | Protein interaction data analysis
Network alignment (NA) aims to find regions of similarities between species’ molecular networks. There exist two NA categories: local (LNA) and global (GNA). LNA finds small highly conserved network regions and produces a many-to-many node mapping.
A fast and scalable local network alignment tool for the identification of functionally conserved modules in multiple networks. To evaluate the performance and the statistical significance, LocalAli were tested on 26 real datasets and 1040 randomly generated datasets. The results suggest that LocalAli outperforms all existing algorithms in terms of coverage, consistency and scalability, meanwhile retains a high precision in the identification of functionally coherent subnetworks.
Allows simultaneous visualization and comparison of multiple networks. In addition to computing generic graph properties for individual networks, CompNet allows multigraph comparisons and similarity based grouping of networks. It also allows visual identification and selection of sub-graphs/communities of interest, enabling a general user to work with and compare between sufficiently complex and large networks. CompNet is a valuable tool for biologists and other researchers working in the field of visual data mining.
A web system for managing, comparing and mining multiple networks, both directed and undirected. tYNA provides five main types of functionality: (1) network management: storing, retrieving and categorizing networks. A comprehensive set of widely used network datasets is preloaded, put into standard form, and categorized with a set of tags; (2) network visualization: displaying networks in an interactive graphical interface; (3) network comparison and manipulation: various kinds of filtering and multiple network operations; (4) network analysis: computing various statistics for the whole network and subsets, and finding motifs and defective cliques; (5) network mining: predicting one network based on the information in another.
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 algorithm that performs a dual alignment strategy, in which both region-to-region alignment and protein-to-protein alignment are performed to achieve superior-quality network alignment. Dual network alignment is achieved in DualAligner via background information provided by a combination of Gene Ontology annotation information and protein interaction network data.
Allows identifying protein complexes in protein-protein interaction (PPI) networks. NetworkBlast-M analyzes networks from multiple species and outputs a set of complexes that are evolutionarily conserved across the networks. NetworkBLAST-M is available for download. It is an implementation of the web-server platform NetworkBLAST for multiple analysis.
The identification of protein complexes is a fundamental challenge in interpreting protein-protein interaction data. Cross-species analysis allows coping with the high levels of noise that are typical to these data. The NetworkBLAST web-server provides a platform for identifying protein complexes in protein-protein interaction networks. It can analyze a single network or two networks from different species. In the latter case, NetworkBLAST outputs a set of putative complexes that are evolutionarily conserved across the two networks.
A protein-protein interaction networks (PPINs) alignment method which combines information from protein sequence, function and network topology. Alignment of human and yeast PPINs reveals several conserved subnetworks between them that participate in similar biological processes, notably the proteasome and transcription related processes. PINALOG has been tested for its power in protein complex prediction as well as function prediction. Comparison with PSI-BLAST in predicting protein function in the twilight zone also shows that PINALOG is valuable in predicting protein function.
A web-based tool designed to enable comparative analysis of protein interaction networks (PINs). NetAlign compares a query PIN with a target PIN by combining interaction topology and sequence similarity to identify conserved network substructures (CoNSs), which may derive from a common ancestor and disclose conserved topological organization of interactions in evolution.
Adds a functionality to PathVisio software, allowing the creation of bioregulatory networks according to MIM notation. PathVisio-MIM is an open source standalone application that integrates a Molecular Interaction Maps (MIM) Glyphs panel into PathVision’ interface that authorizes to use MIM glyphs as well as annotate interactions on diagrams with comments and literature reference information. Besides, it allows users to import and export in MIMML exchange format.
Enables network phylogeny reconstruction. Netdis consists of a topology-based distance measure between networks. The software compares the subgraph content not of the networks themselves but instead of the ensemble of all protein neighborhoods (ego-networks) in each network, through an averaging many-to-many approach. It can separate different random graph model types independent of network size and density.
Adds a functionality to PathVisio software allowing to report errors detected on pathway diagrams against the targeted notation that the platform is able to draw. PathVisio-Validator provides a set of standard rule sets for languages such as Groovy and authorizes the use of customized rulesets. Besides, the module had been developed to be easily extended to various notations added to PathVisio.
Provides one-to-many alignments of reactions in a pair of metabolic pathways. When compared with a state-of-the-art alternative, the CAMPways algorithm provides better alignment results on metabolic networks as far as measures based on same-pathway inclusion and biochemical significance are concerned. The execution speed of CAMPways constitutes yet another important improvement over alternative algorithms.
Evaluates local network alignment (LNA) against global network alignment (GNA). LNA_GNA method provides guidelines for researchers to properly demonstrate the superiority of a newly proposed network alignment (NA) method. LNA aims to find small highly conserved network regions and produces many-to-many mapping between nodes of the compared networks, while GNA aims to find large conserved subgraphs and produces one-to-one node mapping. Given the different outputs of LNA and GNA, when a new NA method is proposed, it is compared against existing methods from the same category.
An algorithm that solves the simultaneous prediction and alignment of networks problem in accordance with its simultaneous nature. Bearing the same name as the defined problem itself, the SiPAN algorithm employs state-of-the-art alignment and topology-based interaction confidence construction algorithms, which are used as benchmark methods for comparison purposes as well.
Allows users to study local similarity analysis (LSA). fastLSA is an algorithm using a novel asymptotic upper bound algorithm for calculating the LSA p-value. It replaces a computationally intensive permutation test to compute significance of LSA statistics with a dramatic increase in the size of datasets that can be analyzed on a single desktop machine. It uses real-world and simulated time series datasets from different fields of inquiry, for visualizing the resulting clusters of local similarity.
An algorithm that, given the networks of two organisms, uncovers subnetworks of proteins that relate in biological function and topology of interactions. The discovered conserved subnetworks have a general topology and need not to correspond to specific interaction patterns, so that they more closely fit the models of functional complexes proposed in the literature. The algorithm is able to handle sparse interaction data with an expansion process that at each step explores the local topology of the networks beyond the proteins directly interacting with the current solution.
Detects molecular systems in genome data. MacSyFinder identifies the presence of a given system according to specifications of the input biological model. It determines the presence of a given component by similarity search with hidden Markov models (HMM) protein profiles using program Hmmer. This tool ignores phylogenetic information when putting together components of systems scattered in a replicon or in unordered datasets.
An algorithm for multiple local network alignment based on statistical iterative sampling in connection to a greedy strategy. GASOLINE can compute and visualize local alignments in a user-friendly way, without requiring postprocessing operations. Alignments can also be analyzed, by annotating proteins with corresponding GO categories, provided as input by the user. GASOLINE overcomes the limits of current approaches by producing biologically significant alignments within a feasible running time, even for very large input instances. The method has been extensively tested on a database of real and synthetic biological networks. A comprehensive comparison with state-of-the art algorithms clearly shows that GASOLINE yields the best results in terms of both reliability of alignments and running time on real biological networks and results comparable in terms of quality of alignments on synthetic networks.
A network synthesis model that can generate families of evolutionarily related synthetic protein-protein interaction (PPI) networks. The proposed model can serve as an effective framework for generating comprehensive benchmark datasets that can be used for reliable performance assessment of comparative network analysis algorithms.