Systems Biology is the analysis of the behavior and interaction between the components of a biological system, being an area that has been growing and allowing several types of analysis, such as the modeling of biological processes and simulations. Flux balance analysis (FBA) is a mathematical method used to analyze the metabolic flux of a metabolic network, allowing prediction of the growth rate of an organism or the rate of production of a metabolite of interest. In order to calculate the FBA, it is necessary and essential to use a stoichiometric matrix, a structure that indicates the various components that participate in a reaction (reagents and products) and their relative molecular proportions. This matrix ends up being difficult to be constructed manually, because it demands time for the fact that a metabolic pathway has many reactions and components. In our study, we developed sARCASM (semi-Automatic Reconstruction and Analysis of Stoichometric Matrix), a set of scripts written in Python whose objective is to automate, standardize and reduce calculation time compared to other pipelines that use the FBA. SARCASM assists in the in silico reconstruction of metabolic pathways of interest and uses the annotation information of a target genome so that, through the KEGG database, the orthologous gene groups are obtained, as well as the stoichiometric model, generation of the model in the SBML format and application of the FBA method. The metabolic pathway of fatty acid biosynthesis was used as tests and the organism studied was Exiguobacterium antarcticum B7 and the results obtained were quite approximate when compared with a reference work.
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