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- W3115294611 abstract "The metabolic capabilities of cells determine their biotechnological potential, fitness in ecosystems, pathogenic threat levels, and function in multicellular organisms. Their comprehensive experimental characterization is generally not feasible, particularly for unculturable organisms. In principle, the full range of metabolic capabilities can be computed from an organism's annotated genome using metabolic network reconstruction. However, current computational methods cannot deal with genome-scale metabolic networks. Part of the problem is that these methods aim to enumerate all metabolic pathways, while computation of all (elementally balanced) conversions between nutrients and products would suffice. Indeed, the elementary conversion modes (ECMs, defined by Urbanczik and Wagner) capture the full metabolic capabilities of a network, but the use of ECMs has not been accessible until now. We explain and extend the theory of ECMs, implement their enumeration in ecmtool, and illustrate their applicability. This work contributes to the elucidation of the full metabolic footprint of any cell." @default.
- W3115294611 created "2021-01-05" @default.
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- W3115294611 date "2021-01-01" @default.
- W3115294611 modified "2023-10-03" @default.
- W3115294611 title "Unlocking Elementary Conversion Modes: ecmtool Unveils All Capabilities of Metabolic Networks" @default.
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- W3115294611 doi "https://doi.org/10.1016/j.patter.2020.100177" @default.
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