PROM

PROM predicts metabolic behavior by integrating genome-scale transcriptional regulatory networks with biochemical metabolic networks to quantify effects of genetic or environmental changes.

Key Features:

• Automated Integration: Automates construction and simulation of integrated networks that combine transcriptional regulatory interactions with genome-scale metabolic networks.
• Large-Scale Phenotypic Predictions: Enables large-scale phenotypic predictions across diverse model organisms by simulating network responses to perturbations.
• Probabilistic Approach: Employs a probabilistic framework to account for uncertainties in regulatory interactions and to improve robustness of metabolic predictions.

Scientific Applications:

• Predictive Modeling: Predicts how genetic or environmental changes influence metabolic pathways and phenotypic outcomes.
• Systems Biology Research: Integrates transcriptional regulation with metabolism to analyze regulatory influences on metabolic behavior in systems biology studies.
• Model Organism Studies: Applies across multiple model organisms to support comparative analyses of regulatory–metabolic interactions.

Methodology:

Automated construction of integrated transcriptional-regulatory and metabolic networks, probabilistic modeling of regulatory interactions, and simulation of metabolic network responses.