GNET2

GNET2 constructs gene regulatory networks from expression data through functional module inference.

Key Features:

• E-M Clustering Process: Clusters genes to functional groups using an expectation-maximization process.
• Iterative TF and Gene Assignment: Iteratively performs transcription factor assigning and gene assigning until gene assignment stabilizes or the maximum number of iterations is reached.

Scientific Applications:

• Gene Regulatory Network Construction: Infers gene regulatory networks from expression data by identifying functional modules.
• Functional Module Inference: Groups genes into functional clusters based on regulatory relationships.

Methodology:

The tool employs an expectation-maximization (E-M) process that iteratively assigns transcription factors and genes until convergence or maximum iterations.