We have developed two genome-scale metabolic network algorithms that integrate the transcriptional regulatory network into genome-scale metabolic models.
PROM (Probabilistic Regulation of Metabolism) enables the quantitative integration of regulatory and metabolic networks to build genome-scale integrated metabolic–regulatory models. GEMINI (Gene Expression and Metabolism Integrated for Network Inference) directly connects regulatory interactions to observable phenotypes and allows rapid assessment of inferred regulatory interactions using a metabolic network.
- Chandrasekaran S and N.D. Price, "Probabilistic integrative modeling of genome-scale metabolic and regulatory networks in Escherichia coli and Mycobacterium tuberculosis," PNAS, 2010.
- Simeonidis E, Chandrasekaran S, Price ND. “A guide to integrating transcriptional regulatory and metabolic networks using PROM (Probabilistic Regulation of Metabolism)”, Methods in Molecular Biology: Systems Metabolic Engineering.
- Chandrasekaran S and N.D. Price, “Metabolic Constraint-based Refinement of Transcriptional Regulatory Networks”, PLOS Computational Biology, 2013.