APPLICATION CATEGORY - PATHWAY/NETWORK ANALYSIS

This set of applications performs the complex task of building and visualizing the potential interactions between gene products leveraging databases of published literature. Typically lists of affected genes from a completed microarray experiment are fed into these applications. This class of tools can provide the greatest biological insight to the end user due to the focus on visualizing the dynamic interactions between gene products and their spatial distribution within the cell.

Ariadne Genomics' PathwayStudio®
PathwayStudio | Technical Specifications | Support | Demo | Sales | Ariadne

PathwayStudio® (formerly known as PathwayAssist) software helps you to interpret microarray data in the context of pathways, as well as construct your own regulatory networks and protein-protein interaction maps. You can classify and prioritize proteins, analyze pathways, export, import and filter data, and automatically update pathways with newly published information. With PathwayStudio,
you can:

     • Identify relationships among proteins, small molecules, cell processes and treatments
     • Reconstruct pathways from your microarray and other experimental data
     • Automatically extract biological interactions from scientific literature

PathwayStudio comes with proprietary ResNet database of functional relationships between proteins, genes, cell objects, drugs, and diseases, automatically extracted from scientific literature. ResNet includes 1000+ reconstructed pathways, and over a million relationships (the complete collection is supplied with the client-server version). The software also works with leading public and commercial databases of signaling and biochemical pathways, including KEGG, BIND, GO, STKE Connections Maps and Prolexys HyNet™.

The ExPlain™ Analysis System from BIOBASE
ExPlain | TRANSFAC® | Support | Sales | BIOBASE

The ExPlain Analysis System applies a new knowledge driven approach to the analysis of whole complexes of coexpressed genes. The internal Composite Module Analyst (CMA) is a genetic algorithm for analysis and prediction of relevant promoters in the identified set of given genes obtained for sources such as Affymetrix GeneChip® Arrays. This combinatorial analysis drops false positive rates significantly and enables scientists to find potential causes for specific cellular events.

The power of correct prediction in ExPlain is driven by TRANSFAC®, a knowledge base of high quality, expert level, manually curated published scientific literature. TRANSFAC presents data on transcription factors, their experimentally-proven binding sites, and regulated genes.

GeneGo's MetaCore
MetaCore | Technical Specs | Support | Sales | Demo | GeneGo

MetaCore™ enables life science researchers to analyze microarrays, SAGE, proteomics, metabolomics and phenotypic experimental data in the context of biological mechanisms in norm and disease. The platform is based on the most comprehensive up to date, expert curated database of "small experiments", mammalian protein interactions, enzymatic reactions and bioactive molecules (drugs, metabolites and toxins). This includes millions of data points. The content includes the largest collection of unique maps with thousands of signaling, regulation and metabolic pathways established for human. Our customers are empowered by an intuitive analytical toolkit for data import, visualization and exchange; with eight unique networking algorithms, multiple specificity filters and a networks comparison module. MetaCore™ is available via web access and as a stand-alone server for in-house installations.

Genomatix's BiblioSphere Pathway Edition
BiblioSpherePE | Technical Specs | Demo | Support | Sales | Genomatix

Dynamic data-driven gene network construction and analysis based on Genomatix Knowledge Base Ontology, literature, and sequence analysis. BiblioSphere PE automatically creates the entire network of biological connections between input and correlated genes. The user is supported by various tools to facilitate focusing on functional sub-nets. He is assisted in finding the biological context most relevant for his research. There is no size limit for networks to be analyzed. Integration of sequence analysis provides additional independent lines of evidence. This is achieved by applying Genomatix' proprietary genome annotation and its unique promoter and transcription factor binding site database.