MetaCore and Key Pathway Advisor

Data-mining and pathway analysis

Description:

MetaCore is a comprehensive systems biology analysis suite that provides 100% manually-curated interaction, disease association, and other biological knowledge. This information can be used to perform: pathway enrichment, network building, target discovery, mechanism of action reconstruction, biomarker identification, sample comparison, patient stratification, and variant analysis. MetaCore displays the results in a graphical and visual way, which allows simultaneous interpretation using built-in analytics for one or more experiments measured with methods such as: 

Microarray SAGE Metabolomics
RNA-Seq Myriad RBM miRNA
Variants/CNV siRNA NanoString
Proteomics Somalogic qPCR


MetaCore provides intuitive access to knowledge captured from the peer-reviewed literature including:

  • Transcription factors, receptors, ligands, kinases, phosphatases, endogenous metabolites, and other molecular classes.
  • Species-specific directional interactions between protein-protein (735k+ interactions), protein-RNA (120k+ interactions), drug-target (625k+ interactions), and gene-disease associations (20k+ genes and 2.5k diseases).
    • Human, mouse, and rat genes in network (23k+, 20k+, and 17k+ respectively) with more than 1.6 million total interactions
  • Signaling and metabolic pathways represented on maps and networks.
    • Over 630 classical signaling pathways
    • More than 170 metabolite signaling pathways
    • Over 640 disease-specific maps (283 in oncology, 154 in lung diseases, 57 in neurodegeneration and mental disease, 54 in nutritional and metabolic disease, and more)
  • Rich integration with public ontologies for diseases using Medical Subject Headings (MeSH) and processes using Gene Ontology (GO) with hierarchical or graphic output.
  • Store and share your data and results on our secure servers to improve collaboration

Simplified “-Omics” data analysis with:

Key Pathway Advisor (KPA)

  • Runs Causal Reasoning to predict upstream drivers of differentially-expressed genes
  • Provides access for biologists and bioinformaticians through a simple web-based interface
  • Upload gene expression and variant data
  • Results presented in the browser and in an intuitive interactive report

Genomic Analysis Tools (GAT)

  • Delivers web-based access to analyze variants in the context of: cohorts, tumor-normal pairs, and pedigrees (trios)
  • Allows filtering and annotation of variants in a Variant Call Format (VCF file) with more than 70 attributes including:
    • Allele frequencies from populations included the 1000 Genomes Project and Exome Sequencing Project, predicted effect on protein function (SIFT, PolyPhen2, logistic regression), conservation score (PhyloP, GERP++), presence in dbSNP, chromosomal location, variants with manually-curated association with disease or drug response, etc.