TPD

TPD detects tipping points in biological processes from high-dimensional time-series or stage-course omics data using dynamic network biomarker (DNB) analysis to identify critical transitions and leading molecular networks.

Key Features:

• Tipping Point Detection: Detects tipping points during dynamic biological processes from high-dimensional time-series or stage-course omics data and reports statistical significance with P values.
• Dynamic Network Biomarker (DNB) Analysis: Implements computational methods grounded in DNB theory to identify leading molecules and networks associated with critical transitions.
• Identification of Key Genes and Functional Annotation: Identifies key genes implicated in the tipping point and provides their associated functional biological information.
• Dynamic Network Tracking: Tracks dynamic changes in the DNB/leading network across stages or time points surrounding the critical transition.
• Survival Analysis and 'Dark' Gene Detection: Performs survival analysis based on DNB scores to uncover 'dark' genes that are nondifferential by expression but differential by DNB score.

Scientific Applications:

• Disease Progression: Identification of critical transitions in disease progression to inform timing of intervention.
• Developmental Biology: Detection of critical states in developmental trajectories and stage-course processes.
• Complex Biological Systems and Therapeutic Insight: Characterization of underlying molecular networks at tipping points to suggest potential pathways for therapeutic intervention and to assess system resilience or vulnerability.

Methodology:

Applies DNB theory to high-dimensional time-series or stage-course omics data to identify leading molecules/networks, compute DNB scores, assess tipping points with P values, and perform survival analysis on DNB scores to detect 'dark' genes.