Community Analyzer is a GUI based Comparative Metagenomic Analysis platform that can be used to perform interactive ‘on the fly’ analysis of a given set of metagenomes on a PC/laptop with modest hardware configurations.
FNV (Flashed-based Network Viewer) is for the visualization of small to moderately sized biological networks and pathways. FVN can also be used to embed pathways inside PDF files for the communication of pathways in soft publication materials
canEvolve query functionalities are designed to fulfill most frequent analysis needs of cancer researchers with a view to generate novel hypotheses. canEvolve stores gene, microRNA (miRNA) and protein expression profiles, copy number alterations for multiple cancer types, and protein-protein interaction information. canEvolve allows querying of results of primary analysis, integrative analysis and network analysis of oncogenomics data. The querying for primary analysis includes differential gene and miRNA expression as well as changes in gene copy number measured with SNP microarrays. At present canEvolve provides different types of information extracted from 90 cancer genomics studies comprising of more than 10,000 patients. The presence of multiple data types, novel integrative analysis for identifying regulators of oncogenesis, network analysis and ability to query gene lists/pathways are distinctive features of canEvolve. canEvolve will facilitate integrative and meta-analysis of oncogenomics datasets.
OrthoClust is a clustering algorithm built on a multilayer network framework. It concatenates networks from individual species by their orthology relationships, arriving at a multiplex network. By optimizing the a generalized modularity function, OrthoClust returns a set of modules that could be either conserved or species-specific.
PubNet is a utility that extracts several types of relationships returned by PubMed queries and maps them into networks, allowing for graphical visualization, textual navigation, and topological analysis. PubNet supports the creation of complex networks derived from the contents of individual citations, such as genes, proteins, Protein Data Bank (PDB) IDs, Medical Subject Headings (MeSH) terms, and authors.
CrossTalkZ is a statistical method and software to assess the significance of crosstalk enrichment between pairs of gene or protein groups in large biological networks.