PathMe

PathMe integrates pathway knowledge from three major pathway databases into a unified Biological Expression Language (BEL) representation to harmonize pathway information and enable comparative analysis of molecular pathways.

Key Features:

• Unified Abstraction Using BEL: Uses Biological Expression Language (BEL) to transform pathway knowledge from three major pathway databases into a unified schema.
• Database-Level Integration: Consolidates pathway landscapes from disparate databases into a coherent, database-level integrated representation.
• Pathway-Level Consensus Comparison: Computes and compares consensus at the pathway level across different databases to identify agreements and discrepancies.
• Exploration of Pathway Crosstalk: Enables analysis of pathway crosstalk at the molecular level to investigate interactions and shared molecules across pathways.

Scientific Applications:

• Systems Biology: Supports systems-level interpretation of complex biological interactions by providing integrated pathway representations.
• Multi-omics Interpretation: Enhances interpretation of multi-omics experiments by consolidating pathway information across databases.
• Biomarker and Therapeutic Target Discovery: Facilitates identification of potential biomarkers and therapeutic targets through comprehensive pathway comparison.
• Cross-database Harmonization for Collaborative Research: Facilitates collaborative research by harmonizing pathway information across different pathway databases.

Methodology:

Implemented as a Python package that leverages Biological Expression Language (BEL) to transform and integrate pathway data from three major pathway databases, performs database-level integration, pathway-level consensus comparison, and exploration of pathway crosstalk.