Literature DB >> 12832147

Optimization of biochemical systems by linear programming and general mass action model representations.

Alberto Marín-Sanguino1, Néstor V Torres.   

Abstract

A new method is proposed for the optimization of biochemical systems. The method, based on the separation of the stoichiometric and kinetic aspects of the system, follows the general approach used in the previously presented indirect optimization method (IOM) developed within biochemical systems theory. It is called GMA-IOM because it makes use of the generalized mass action (GMA) as the model system representation form. The GMA representation avoids flux aggregation and thus prevents possible stoichiometric errors. The optimization of a system is used to illustrate and compare the features, advantages and shortcomings of both versions of the IOM method as a general strategy for designing improved microbial strains of biotechnological interest. Special attention has been paid to practical problems for the actual implementation of the new proposed strategy, such as the total protein content of the engineered strain or the deviation from the original steady state and its influence on cell viability.

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Year:  2003        PMID: 12832147     DOI: 10.1016/s0025-5564(03)00046-4

Source DB:  PubMed          Journal:  Math Biosci        ISSN: 0025-5564            Impact factor:   2.144


  4 in total

1.  Identifying the preferred subset of enzymatic profiles in nonlinear kinetic metabolic models via multiobjective global optimization and Pareto filters.

Authors:  Carlos Pozo; Gonzalo Guillén-Gosálbez; Albert Sorribas; Laureano Jiménez
Journal:  PLoS One       Date:  2012-09-20       Impact factor: 3.240

2.  Steady-state global optimization of metabolic non-linear dynamic models through recasting into power-law canonical models.

Authors:  Carlos Pozo; Alberto Marín-Sanguino; Rui Alves; Gonzalo Guillén-Gosálbez; Laureano Jiménez; Albert Sorribas
Journal:  BMC Syst Biol       Date:  2011-08-25

3.  A newton cooperative genetic algorithm method for in silico optimization of metabolic pathway production.

Authors:  Mohd Arfian Ismail; Safaai Deris; Mohd Saberi Mohamad; Afnizanfaizal Abdullah
Journal:  PLoS One       Date:  2015-05-11       Impact factor: 3.240

4.  Identifying quantitative operation principles in metabolic pathways: a systematic method for searching feasible enzyme activity patterns leading to cellular adaptive responses.

Authors:  Gonzalo Guillén-Gosálbez; Albert Sorribas
Journal:  BMC Bioinformatics       Date:  2009-11-24       Impact factor: 3.169

  4 in total

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