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FreeFlux: A Python Package for Time-Efficient Isotopically Nonstationary Metabolic Flux Analysis
[Image: see text] (13)C metabolic flux analysis is a powerful tool for metabolism characterization in metabolic engineering and synthetic biology. However, the widespread adoption of this tool is hindered by limited software availability and computational efficiency. Currently, the most widely accep...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
American Chemical Society
2023
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10510750/ https://www.ncbi.nlm.nih.gov/pubmed/37561998 http://dx.doi.org/10.1021/acssynbio.3c00265 |
Sumario: | [Image: see text] (13)C metabolic flux analysis is a powerful tool for metabolism characterization in metabolic engineering and synthetic biology. However, the widespread adoption of this tool is hindered by limited software availability and computational efficiency. Currently, the most widely accepted (13)C-flux tools, such as INCA and 13CFLUX2, are developed in a closed-source environment. While several open-source packages or software are available, they are either computationally inefficient or only suitable for flux estimation at isotopic steady state. To address the need for a time-efficient computational tool for the more complicated flux analysis at an isotopically nonstationary state, especially for understanding the single-carbon substrate metabolism, we present FreeFlux. FreeFlux is an open-source Python package that performs labeling pattern simulation and flux analysis at both isotopic steady state and transient state, enabling a more comprehensive analysis of cellular metabolism. FreeFlux provides a set of interfaces to manipulate the objects abstracted from a labeling experiment and computational process, making it easy to integrate into other programs or pipelines. The flux estimation by FreeFlux is fast and reliable, and its validity has been confirmed by comparison with results from other computational tools using both synthetic and experimental data. FreeFlux is freely available at https://github.com/Chaowu88/freeflux with a detailed online tutorial and documentation provided at https://freeflux.readthedocs.io/en/latest/index.html. |
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