predictionet

predictionet infers predictive gene networks from gene expression profiles and known gene interaction data to model molecular mechanisms underlying phenotypes.

Key Features:

• Integration of Multiple Data Types: Combines gene expression profiles with known gene interaction data aggregated from publicly available repositories to construct comprehensive gene networks.
• Predictive Network Framework (PN): A flexible framework for analysis and visualization of gene interaction networks that supports evaluation of experimentally derived gene lists within large-scale networks.
• Analytical Pipeline: Implements a two-step analytical pipeline that collects known gene interactions from public sources and integrates them with gene expression data for network inference.

Scientific Applications:

• Mechanism elucidation: Infers gene networks to elucidate molecular mechanisms underlying different phenotypes.
• Predictive evaluation: Assesses the predictive power of inferred networks to evaluate the biological relevance of gene interactions.

Methodology:

Aggregates known gene interactions from public repositories and integrates these interactions with experimental gene expression data to infer predictive gene networks.