Pathway crosstalk network prediction software tools | Protein interaction data analysis
Cells communicate with their environment via signal transduction pathways. On occasion, the activation of one pathway can produce an effect downstream of another pathway, a phenomenon known as crosstalk.
Constructs clusters greedily, starting from local seeds that have high weighted degree, and adding nodes that maintain the density of the clusters. SPICi is based on a simpler cluster expansion approach, employs a different seed selection criterion and incorporates interaction confidences. It shows good performance in recapitulating protein complexes, deteriorating only on extremely incomplete networks. This tool is robust to perturbations in dense functional networks.
A statistical method and software to assess the significance of crosstalk enrichment between pairs of gene or protein groups in large biological networks. We demonstrate that the standard z-score is generally an appropriate and unbiased statistic. We further evaluate the ability of four different methods to reliably recover crosstalk within known biological pathways. We conclude that the methods preserving the second-order topological network properties perform best. Finally, we show how CrossTalkZ can be used to annotate experimental gene sets using known pathway annotations and that its performance at this task is superior to gene enrichment analysis (GEA).
A genome wide network analysis tool. BinoX determines the statistical significance of network link enrichment or depletion between gene sets, using the binomial distribution. It may be employed for any type of gene set analysis as long as a comprehensive functional association network exists for the genes. BinoX offers superior performance compared to existing methods in terms of true positive and false positive rates (FPRs).
Assists users in understanding association and interrelation of age-related disorders (ARDs) and associated proteins, pathways, and drugs. ARDnet allows construction of networks of ARDs associated proteins, drugs, and pathways and provides a methodology for analyzing and visualizing ARDs related data. This tool incorporates several age-related disorders and their associated proteins information as well as information about drugs and their ARDs protein targets.
Assists in navigating large interaction networks by linking two nodes or two groups of nodes with each other. viPEr is a Cytoscape plugin that integrates omics data with interactome data. It can be used to identify potential links between processes or pathways. It also enables users to explore the neighborhood of a single node with respect to the numerical quality of radiating paths.
Trains and evaluates knowledge graph embeddings (KGEs) on biological knowledge graphs (KGs). BioKEEN consists of three layers: (1) the model configuration layer, (2) the data acquisition and transformation layer, and (3) the learning layer. The software enables users without expert knowledge in machine learning to learn and apply biological based KGE. It was tested on several KGE models on the pathway mappings from ComPath.
Integrates content from publicly accessible pathway databases, generates comparisons, and simplifies curation of inter-database mappings. ComPath can produce summary tables and create several visualizations to enable exploration of the distributions of pathway size and gene memberships for each database. This tool can be used to detect effects such as genetic promiscuity or differences in the size distribution of gene sets.