OBIF

OBIF implements a systems-level analysis framework to identify molecular drivers of supra-additive (synergistic) interactions from multi-omics data for studying combination therapies.

Key Features:

• Integration of Statistical and Biological Interactions: OBIF combines statistical analysis with biological context to identify supra-additive interactions in complex responses.
• Full Factorial Analysis: The framework performs full factorial analysis on feature expression data from single and dual factor exposures to detect molecular clusters mediating synergy.
• Multi-Omics Data Compatibility: OBIF analyzes transcriptomics and proteomics datasets to provide a cross-platform view of molecular interactions.
• Phenotype-Driven Approach: The framework links phenotypic outcomes to pathways, functions, and regulators that contribute to synergistic effects.

Scientific Applications:

• Therapeutic Combination Screening: OBIF has been used to screen bioactive molecule libraries to identify effective therapeutic combinations.
• Immunostimulatory Dyad Analysis: The framework was applied to a therapeutic dyad of immunostimulatory small molecules that provided synergistic protection against influenza A pneumonia.
• Regulatory Mechanism Discovery: Using transcriptomic and proteomic analysis, OBIF identified cooperation between RelA and cJun as critical for the observed antiviral synergy.

Methodology:

Combining data from different omics platforms; applying full factorial analysis to feature expression data from single and dual exposures to identify molecular clusters driving synergistic responses; and confirming identified pathways through experimental validation as reported.