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Auflistung nach Autor:in "Kaleta, Christoph"

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  • Konferenzbeitrag
    CASOP GS: computing intervention strategies targeted at production improvement in genome-scale metabolic networks
    (German Conference on Bioinformatics 2010, 2010) Bohl, Katrin; Figueiredo, Luís F. de; Hädicke, Oliver; Klamt, Steffen; Kost, Christian; Schuster, Stefan; Kaleta, Christoph
    Metabolic engineering aims to improve the production of desired biochemicals and proteins in organisms and therefore, plays a central role in Biotechnology. However, the design of overproducing strains is not straightforward due to the complexity of metabolic and regulatory networks. Thus, theoretical tools supporting the design of such strains have been developed. One particular method, CASOP, uses the set of elementary flux modes (EFMs) of a reaction network to propose strategies for the overproduction of a target compound. The advantage of CASOP over other approaches is that it does not consider a single specific flux distribution within the network but the whole set of possible flux distributions represented by the EFMs of the network. Moreover, its application results not only in the identification of candidate loci that can be knocked out, but additionally proposes overexpression candidates. However, the utilization of CASOP was restricted to small and medium scale metabolic networks so far, since the entire set of EFMs cannot be enumerated in such networks. This work presents an approach that allows to use CASOP even in genome-scale networks. This approach is based on an estimation of the score utilized in CASOP through a sample of EFMs within a genome-scale network. Using EFMs from the genome-scale metabolic network gives a more reliable picture of the metabolic capabilities of an organism required for the design of overproducing strains. We applied our new method to identify strategies for the overproduction of succinate and histidine in Escherichia coli. The succinate case study, in particular, proposes engineering targets which resemble known strategies already applied in E. coli. Availability: Source code and an executable are available upon request.
  • Konferenzbeitrag
    EFMEvolver: Computing elementary flux modes in genome-scale metabolic networks
    (German conference on bioinformatics 2009, 2009) Kaleta, Christoph; Figueiredo, Luís Filipe de; Behre, Jörn; Schuster, Stefan
    Elementary flux mode analysis (EFM analysis) is an important method in the study of biochemical pathways. However, the computation of EFMs is limited to small and medium size metabolic networks due to a combinatorial explosion in their number in larger networks. Additionally, the existing tools to compute EFMs require to enumerate all EFMs before selecting those of interest. The method presented here extends EFM analysis to genome-scale models. Instead of computing the entire set of EFMs an optimization problem is used to determine a single EFM. Coupled with a genetic algorithm (GA) this allows to explore the solution space and determine specific EFMs of interest. Applied to a network in which the set of EFMs is known our method was able to find all EFMs in two cases and in another case almost the entire set before aborted. Furthermore, we determined the parts of three metabolic networks that can be used to produce particular amino acids and found that these parts correspond to significant portions of the entire networks. Availability: Source code and an executable are available upon request.