Escher

Escher visualizes data on biological pathways, including metabolic maps, by enabling users to rapidly design new pathway maps, overlay multi-omics data on reactions and pathways, and create adaptable web-based visualizations.

Key Features:

• Semi-automated pathway map design: Escher provides pathway suggestions based on user data and genome-scale models to accelerate the creation of new pathway maps.
• Multi-omics data visualization: Users can visualize data related to genes or proteins on associated reactions and pathways using rules that define which enzymes catalyze each reaction, supporting RNA-Seq, proteomics, ChIP, metabolomics, and fluxomics data types.
• Web-based visualization framework: Escher uses SVG, D3, and developer tools to enable rapid adaptation, extension, sharing, and embedding of pathway visualizations.

Scientific Applications:

• Metabolic pathway mapping: Users can build, view, and share metabolic maps based on genome-scale metabolic models.
• Integrated multi-omics analysis: Researchers can identify trends across genomic, transcriptomic, proteomic, metabolomic, and fluxomic data types in the context of biological pathways.
• Enzyme-reaction association analysis: Users can apply rules defining enzyme catalysis to interpret gene and protein data in relation to metabolic reactions.

Methodology:

Escher uses SVG and D3 web technologies for rendering pathway visualizations, provides pathway suggestions based on user data and genome-scale models for semi-automated map drawing, and applies rules defining which enzymes catalyze each reaction to map gene and protein data onto reactions and pathways.