GeneNetFinder

GeneNetFinder infers dynamic gene regulatory interactions from time-series gene expression data to characterize temporal and combinatorial regulation across cell cycle stages.

Key Features:

• Dynamic Interaction Identification: Identifies gene regulatory interactions that change across cell cycle stages, capturing both individual and combined regulator effects.
• Temporal Aspects Analysis: Determines the order and pace of regulatory interactions over time from time-series expression data.
• Multiple Regulator Detection: Detects genes regulated by multiple factors acting independently or combinatorially.
• Dynamic Network Representation: Represents regulatory relationships as dynamic networks that illustrate changes across different cell cycle phases.

Scientific Applications:

• Modeling complex regulatory systems: Enables modeling of complex gene regulatory systems involving multiple regulators.
• Studying dynamic biological processes: Facilitates analysis of temporal and combinatorial regulation in dynamic processes such as cell cycle progression.
• Revealing non-apparent interactions: Reveals regulatory interactions that are not apparent from static analyses.

Methodology:

Uses time-series gene expression data and two score types, R1 and R2, to quantify regulatory interactions and their temporal characteristics and to identify single and multiple regulator scenarios.