Augusta

Augusta infers gene regulatory networks (GRNs) and Boolean networks (BNs) from high-throughput gene expression data such as RNA-Seq to model genome-wide regulatory interactions.

Key Features:

• Gene Regulatory Network Inference: Reconstructs gene regulatory networks from gene expression datasets.
• Transcription Factor Motif Integration: Refines predicted regulatory interactions by identifying transcription factor binding motifs in promoter regions and incorporating verified interactions from databases.
• Boolean Network Construction: Converts inferred gene regulatory networks into Boolean network models with logical rules governing regulatory interactions.
• SBML Model Generation: Exports Boolean network models in Systems Biology Markup Language (SBML) format for further analysis and editing.
• Applicability to Non-Model Organisms: Enables regulatory network inference even when organism-specific information is not available in existing databases.

Scientific Applications:

• Gene Regulatory Network Analysis: Investigates genome-wide regulatory interactions inferred from gene expression datasets.
• Systems Biology Modeling: Enables construction of Boolean network models for analysis of gene regulatory dynamics.
• Microbial and Non-Model Organism Research: Supports regulatory network reconstruction in organisms lacking extensive regulatory annotations.

Methodology:

Augusta infers gene regulatory networks from gene expression data, refines regulatory interactions using transcription factor binding motif prediction and database-supported interactions, and converts the resulting network into a Boolean network model with logical rules exported in SBML format.