DEAP

DEAP analyzes differential gene and protein expression data within biological pathways to identify significantly altered pathway segments and regulatory patterns.

Key Features:

• Pathway Structure Integration: Incorporates biological pathway topology to evaluate differential expression within interconnected gene and protein networks.
• Sub-Pathway Identification: Detects the most differentially expressed segments within larger biological pathways.
• Enhanced Detection Sensitivity: Increases statistical power for identifying pathway-level differential expression in both high and low differential expression scenarios.
• Disease-Associated Pathway Detection: Identifies biologically relevant pathways and pathway segments associated with experimental conditions such as chronic obstructive pulmonary disease (COPD) and interferon treatment.

Scientific Applications:

• Pathway-Level Differential Expression Analysis: Enables identification of regulatory pathway segments affected by gene or protein expression changes.
• Disease Mechanism Investigation: Supports discovery of pathways associated with disease states such as COPD.
• Signal Transduction Analysis: Facilitates analysis of pathway components including signaling networks such as the Notch signaling pathway.

Methodology:

DEAP integrates differential gene or protein expression data with biological pathway structure information to identify significantly altered pathway segments and regulatory patterns.