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Pathway Analysis & Data Mining for Gene Expression

Available on MAC or PC!    MS Internet Explorer,  FireFox,  Safari and  Chrome compatible.

MetaCore™ is an integrated knowledge database and software suite for pathway analysis of experimental data and gene lists. The scope of data types includes microarray and sequence-based gene expression, SNPs and CGH arrays, proteomics, metabolomics, Co-IP pull-out and other custom interactions. MetaCore™ is based on a proprietary manually curated database of human protein-protein, protein-DNA and protein compound interactions, metabolic and signaling pathways for human, mouse and rat, supported by proprietary ontologies and controlled vocabulary. The analytical package includes easy to use, intuitive tools for search, data visualization, mapping and exchange, biological networks and interactome. MetaCore™ includes MetaRodent™, MetaLink™ and MetaSearch™. MetaCore™ is available in two business models:

• Web portal access — Named or concurrent licenses that provide access to pathway analysis applications via the company’s secure server using the Internet protected by Verisign.
• Enterprise solution — Installation of MetaCore&trade behind the customer’s firewall for pathway analysis research. MetaCore™ becomes part of the intranet network and can be used as an internal informatics system. In house installations give customers hierarchical access to accounts, group sharing, and behind-the-firewall data exchange security.

Annual or multi-year licenses are available for this pathway analysis application.

Product highlights - Data Mining & Pathway Analysis

• Analyze ANY experimental high-throughput data in the context of pathways, networks and maps - ideal for data mining and pathway analysis applications
• Identify and rank affected pathways and networks for your lists of genes, proteins, transcripts or compounds
• Easy-to-use workflow wizards for data upload, analysis and interpretation for pathway analysis, gene expression and more with a word report as output
• Evaluate risk factors for common and orphan human diseases using manually annotated gene-disease causal associations
• Concurrently visualize and cross-validate different types of data
• Choose from ten network-creating algorithms and multiple filters for optimal data mining
• Take advantage of the annotated content database that took over 100 man-years to assemble
• Over 2,000 interactive maps with consensus knowledge of human biology and diseases
• Visualize mouse, rat, worm, fly, yeast, chimpanzee, bovine, zebrafish, mosquito, mold, rice, arabidopsis, candida, plasmodium and dog data on maps and networks
• Mine your data in real time: multiple data points, conditions, time-series, treatments through animated videos
• Apply disease, tissue, functional processes and sub-cellular localization filters to focus networks on information relevant to study
• Have total control over settings: your choice of ranges, colors, data sets, etc.
• Select, save & export high resolution images of pathways and networks for pathway analysis mapping

Data analysis tools

• Easy to use query for genes, proteins, compounds, reactions, pathways, drugs and diseases
• Combinatorial advanced search in an intuitive interface
• Enrichment analysis in multiple ontologies: GeneGo annotated processes, canonical pathways, GO processes and human diseases
• Statistical tests and scoring for network relevance to the dataset, functional processes, cellular pathways and transcription factors
• Multiple ways to generate networks
  • 10 network-generating algorithms
  • Specificity filters for tissues, functional processes, sub-cellular localization, interaction mechanisms, species etc.
• Unique interactome analysis tools: identify the most relevant transcription factors, kinases, receptors, signaling proteins, phosphatases and enzymes in your datasets
• Multiple types of P-value calculations for enrichment analysis and network prioritization
• Multiple logical operations on networks and gene lists
• Over 7 million resolved synonyms for genes, proteins and compounds
• Custom network editing for all functions

Curated content

• Unique manually curated database of human protein-protein, protein-DNA, Protein-RNA and protein-compounds interactions such as gene expression
• Human endogenous metabolism: enzyme-encoding genes, reactions and metabolites
• “Causal” gene-disease associations for over 500 human diseases and conditions, 4500 genes
• Three domains of human interactions: target-ligand, signaling and signal transduction and core metabolism
• Over 2,000 original canonical pathway analysis maps for signaling and metabolism
• Proprietary GeneGo ontology for cellular and molecular processes and human diseases

Integration, visualization and management of experimental data from pathway analysis to gene expression and beyond

• Universal parser for molecular data: Affymetrix, Agilent, Illumina, GE Healthcare expression arrays, SNP arrays, siRNA and proteomics
• Unique parsers for metabolomics data and custom protein-protein interactions
• Interconnectivity and cross-referencing with P-values between maps, networks and functional processes
• Drug targets and associated drugs
• Disease genetic data and disease networks
• Seamless integration and file exchange with ResolverTM , GeneSpringTM , Spotfire’s Decision Site TM, ArrayTrack, GeneData’s Expressionist and Phylosopher products, Inforsense’s KDE, SciTegic’s Pipeline Pilot, Xenobase and other data analysis packages including our customers internal software and databases
• Instant mapping of multiple, heterogeneous experimental data sets onto functional maps and pathways
• Concurrent visualization of multiple data types on the same maps or networks
• Concurrent visualization of multiple experiments, time points & dosages through animated graphics
• Flexible switching between data sets and controls
• User controls: colors scheme, value ranges, thresholds
• Mapping human, rat, mouse, fly, worm, dog, chicken, chimpanzee and yeast orthologs on maps and networks for pathway analysis solutions
• Password-protected individual and group accounts
• Import/export, store networks, maps and gene lists in different formats
• Comprehensive reports produced from the compare experiments workflow

System design & access for pathway analysis applications

• Oracle database architecture
• Seamless compatibility with customer’s IT infrastructure for comprehensive data mining & pathway analysis applications
• Web-based access or “behind-the-firewall” internal server installation
• Named user or concurrent licenses for pathway analysis

Toxicity Analysis

MetaCore’s Toxicity workflow rapidly identifies perturbations in pathways and processes related to adverse effects from experimental ‘omics data. The workflow includes enrichment analysis for toxicity-related processes in liver, kidney and heart, alongside evaluation of effects on GeneGo Pathway Maps, GO categories, and metabolic and signaling networks. The workflow includes some unique features, including the ability to specify one or more targets to be added to the analysis, which allows for proteins not represented in the uploaded list (for example a known drug target) to be included.

GeneGo pathway maps and networks in MetaCore and MetaDrug comprise metabolic and signaling processes derived from extensive full-text literature annotation of mechanistic interactions between proteins, enzymatic activities and small molecules. This rich functional biology resource (including > 840,000 interactions and > 700 maps) can be used to identify perturbed processes, reconstruct signaling networks “on the fly”, visualize and understand experimental effects on genes, proteins and metabolites and identify and validate putative gene, protein, enzymatic or small molecule biomarkers of toxicity.

More advanced analyses, taking advantage of the many network generation and analysis algorithms in MetaCore can be employed to provide a more focused picture of modes and mechanisms of toxicity. A new MetaCore feature, Interactome Workflow, walks the user through an detailed analysis of the experimentally-derived network, identifying topological features and critical nodes, such as receptors, enzymes, and transcription factors that may not appear to be altered in experimental datasets, but which may represent key mechanistic targets of chemical toxicity.

API

An API is available for MetaCore. Please contact customersupport@genego.com for more information.