TSNI

TSNI infers local gene-gene interaction networks from time-series gene expression profiles using a linear ordinary differential equation framework to elucidate dynamic regulatory relationships surrounding a gene of interest.

Key Features:

• Inference Algorithm: Implements a novel approach based on linear ordinary differential equations (ODEs) to deduce gene-gene interaction networks.
• Time-Series Data Analysis: Analyzes time-series gene expression profiles to recover dynamic regulatory relationships.
• Local Network Focus: Targets and infers interactions in the local vicinity of a selected gene of interest.
• Robustness to Limited Data: Capable of inferring regulatory interactions even with limited measurement data.
• Validation: Validated using in silico simulated gene expression data and empirical data from a nine-gene subnetwork of the SOS pathway.

Scientific Applications:

• Gene Interaction Networks: Reconstruction of local gene-gene interaction networks to study cellular information processing and metabolic regulation.
• DNA-Damage Response Pathway Analysis: Inference of regulatory interactions within the SOS pathway in Escherichia coli, including analyses of a nine-gene subnetwork.

Methodology:

Uses a linear ordinary differential equation (ODE)–based inference algorithm applied to time-series gene expression profiles, validated on in silico simulated data and empirical measurements from a nine-gene SOS subnetwork in Escherichia coli, and demonstrated capacity to operate with limited measurements.