Metabolic network analysis tools

Christensen B and Nielsen J (2000) Metabolic network analysis. A powerful tool in metabolic engineering. Advances in Biochemical Engineering/Biotechnology 66 209-231. 

Fig. 2.1 Tools for metabolic network analysis, (a) Problem Statement The simple depicted network is comprised of internal metabolites A, B, C, D, E, and P linked through the internal reactions (e.g. r, r, r, r, r, and r and external metabolites (e.g. and P J which are transported...

The ability to identify all feasible EMs inherent to a metabolic network with unique properties makes EMA a useful metabolic pathway analysis tool for a wide range of applications including systematic characterization of cellular phenotypes (Beurton-Aimar et al. 2011 Carlson and Srienc 2004a, b Kurata et al. 2007 Larhlimi and Bockmayr 2009 Nookaew et al. 2007 Poolman et al. 2003, 2004 Rajvanshi and Venkatesh 2011 Schwartz and Kanehisa 2005, 2006 Wiback et al. 

EMA is a useful metabolic pathway analysis tool for rational strain design and metabolic pathway evolntion of designed strains. EMA is entirely based on the strnctnral analysis of invariant metabolic networks withont reqniring kinetics parameters or experimental flnx data, snch as substrate uptake or secretion rates, which enables the prediction of genetic modifications (e.g. gene deletion and over- or down-expression) to reprogram microbial metabolic pathways and achieve desirable phenotypes. 

Trinh CT, Wlaschin A, Srienc F (2009) Elementary mode analysis a useful metabolic pathway analysis tool for characterizing cellular metabolism. Appl Microbiol Biotechnol 81 813-826 Trinh CT, 14 J, Blanch H W, Clark DS (2011) Redesigning Escherichia coli metabolism for anaerobic production of isobutanol. Appl Environ Microbiol 77 4894-4904 Unrean P, Srienc F (2011) Metabolic networks evolve towards states of maximum entropy production. Metab Eng 13 666-673... 

Molecular Biology Tools Metabolic Network Analysis Metabolic Control Analysis Tools from Functional Genomics Applications of Metabolic Engineering Future Directions... 

Metabolic network analysis is clearly a very powerful tool for phenotypic characterization. It is, however, important to underline that the technique has no predictive power. Only in few cases do the estimated fluxes by itself point to a strategy for directed genetic modifications. In most cases flux analysis is only useful when different strains are compared or there is performed a comparison of the same strain grown at different environmental conditions (see Fig. 7). Through such comparisons it may be possible to derive correlations between the productivity and certain fluxes, and from such correlations a hypothesis about possible limitations within the cell may be derived. 

Christensen, B., and Nielsen, I. (1999). Metabolic network analysis—Powerful tool in metabolic engineering. Adv. Biochem. EngJBiotechnol. 66, 209-231. 

Tools that are useful in metabolic network analysis are given below ... 

Although the importance of a systemic perspective on metabolism has only recently attained widespread attention, a formal frameworks for systemic analysis has already been developed since the late 1960s. Biochemical Systems Theory (BST), put forward by Savageau and others [142, 144 147], seeks to provide a unified framework for the analysis of cellular reaction networks. Predating Metabolic Control Analysis, BST emphasizes three main aspects in the analysis of metabolism [319] (i) the importance of the interconnections, rather than the components, for cellular function (ii) the nonlinearity of biochemical rate equations (iii) the need for a unified mathematical treatment. Similar to MCA, the achievements associated with BST would warrant a more elaborate treatment, here we will focus on BST solely as a tool for the approximation and numerical simulation of complex biochemical reaction networks. 

Nonetheless, as a tool for analysis and simulation of large-scale metabolic networks the use of approximate kinetics may be criticized for several reasons ... 

Table 3 lists the major advanced computational software tools that are currently used for data analysis, visualization, modeling, simulation, and statistical computing, especially for microbial metabolic networks, models, and omics experiments. The given selection while intended to cover currently available software in this field is subjective, and the reader should consider available literature to focus on the specialized aspects and specific applications of the listed databases and software tools. 

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