Identification of regulatory structure and kinetic parameters of biochemical networks via mixed-integer dynamic optimization
Data de publicació2013
Guillén Gosálbez, Gonzalo
Jiménez Esteller, Laureano
MetadadesMostra el registre d'unitat complet
Background: Recovering the network topology and associated kinetic parameter values from time-series data are central topics in systems biology. Nevertheless, methods that simultaneously do both are few and lack generality. Results: Here, we present a rigorous approach for simultaneously estimating the parameters and regulatory topology of biochemical networks from time-series data. The parameter estimation task is formulated as a mixedinteger dynamic optimization problem with: (i) binary variables, used to model the existence of regulatory interactions and kinetic effects of metabolites in the network processes; and (ii) continuous variables, denoting metabolites concentrations and kinetic parameters values. The approach simultaneously optimizes the Akaike criterion, which captures the trade-off between complexity (measured by the number of parameters), and accuracy of the fitting. This simultaneous optimization mitigates a possible overfitting that could result from addition of spurious regulatory interactions. Conclusion: The capabilities of our approach were tested in one benchmark problem. Our algorithm is able to identify a set of plausible network topologies with their associated parameters.
És part deBMC Systems Biology, 2013, vol. 7, núm. 113, p. 1-11
Projectes de recerca europeus
Els fitxers de llicència següents estan associats amb aquest element:
Aquest document està subjecte a una llicència Creative Commons.cc-by, (c) Guillén Gosálbez et al., 2013
Mostrant elements relacionats per títol, autor i matèria.
Identifying the preferred subset of enzymatic profiles in nonlinear kinetic metabolic models via multiobjective global optimization and pareto filters Pozo Fernández, Carlos; Guillén Gosálbez, Gonzalo; Sorribas Tello, Albert; Jiménez Esteller, Laureano (Public Library of Science (PLoS), 2012)Optimization models in metabolic engineering and systems biology focus typically on optimizing a unique criterion, usually the synthesis rate of a metabolite of interest or the rate of growth. Connectivity and non-linear ...
Steady-state global optimization of metabolic non-linear dynamic models through recasting into power-law canonical models Pozo Fernández, Carlos; Marín-Sanguino, Alberto; Alves, Rui; Guillén Gosálbez, Gonzalo; Jiménez Esteller, Laureano; Sorribas Tello, Albert (BioMed Central, 2011)Background: Design of newly engineered microbial strains for biotechnological purposes would greatly benefit from the development of realistic mathematical models for the processes to be optimized. Such models can then be ...
On the use of filters to facilitate the post-optimal analysis of the Pareto solutions in multi-objective optimization Antipova, Ekaterina; Pozo, C.; Guillén Gosálbez, Gonzalo; Boer, Dieter; Cabeza, Luisa F.; Jiménez Esteller, Laureano (Elsevier, 2015)Multi-objective optimization (MOO) has emerged recently as a useful technique in the design andplanning of engineering systems because it allows identifying alternatives leading to significant envi-ronmental savings. MOO ...