Title: Systems and synthetic biology approaches to benchmark modeling and reverse engineering
Authors: Irene Cantone, Lucia Marucci, Francesco Iorio, Vincenzo Belcastro, Mukesh Bansal, Maria Aurelia Ricci , Stefania Santini, Mario di Bernardo, Maria Pia Cosma Diego di Bernardo
Abstract:Systems Biology approaches are extensively used to model and reverse-engineer gene regulatory networks from experimental data. Conversely, Synthetic Biology allows constructing de novo a regulatory network to seed new functions in the cell. At present, usefulness and predictive ability of modelling and reverse-engineering cannot be assessed and compared rigorously. We built in the yeast Saccharomyces cerevisiae a synthetic network, IRMA, for In-vivo benchmarking of Reverse-engineering and Modelling Approaches. The network is composed of five genes regulating each other through a variety of regulatory interactions; it is negligibly affected by endogenous genes and is responsive to small molecules. We measured promoter strengths, as well as, steady-state and time-series expression data following multiple perturbations. These data were used to assess state-of-the-art modelling and reverse-engineering techniques. A dynamical model of IRMA is able to capture and predict its behaviour; reverse-engineering based on differential equations correctly infers regulatory interactions for informative datasets.
Cantone I, Marucci L, Iorio F, Ricci M, Belcastro V, Bansal M, Santini S, di Bernardo M, di Bernardo D*, Cosma MP*. A Yeast Synthetic Network for In Vivo Assessment of Reverse-Engineering and Modeling Approaches . Cell, Volume 137, Issue 1, 172-181, 26 March 2009
Questions & Comments: