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Supplementary datasets accompanying the manuscript "ARBRE: Computational resource to predict pathways towards industrially important aromatic compounds" published in the Metabolic Engineering Journal (https://doi.org/10.1016/j.ymben.2022.03.013). In line with the standards of open science, the ARBRE toolbox is freely available to the scientific community on gitHub (https://github.com/EPFL-LCSB/ARBRE) and we also provide the web-version at http://lcsb-databases.epfl.ch/arbre/ ARBRE: Aromatic compounds RetroBiosynthesis Repository and Explorer is a new computational resource consisting of a comprehensive biochemical reaction network centered around aromatic amino acid biosynthesis and a computational toolbox for navigating this network. ARBRE encompasses over 33′000 known and 390′000 novel reactions predicted with generalized enzymatic reactions rules and over 74′000 compounds, of which 19′000 are known to biochemical databases and 55′000 only to PubChem. Over 1′000 molecules that were solely part of the PubChem database before and were previously impossible to integrate into a biochemical network are included in the ARBRE reaction network by assigning enzymatic reactions. ARBRE can be applied for pathway search, enzyme annotation, pathway ranking, visualization, and network expansion around known biochemical pathways and products of lignin degradation to predict valuable compound derivations. Supplementary files are organized as follows: - 1-s2.0-S1096717622000490-mmc4.docx contains Supplementary Figures 1-4 and Tables 1, 2, and 4. - 1-s2.0-S1096717622000490-mmc2.xlsx contains Supplementary Table 3. - 1-s2.0-S1096717622000490-mmc1.xlsx contains Supplementary Table 5 - 1-s2.0-S1096717622000490-mmc3.xlsx contains Supplementary Table 6
Enzyme prediction, Pathway prediction, computational resource, aromatic amino acids metabolism, metabolic engineering, database, Synthetic biology, novel biosynthetic pathways
Enzyme prediction, Pathway prediction, computational resource, aromatic amino acids metabolism, metabolic engineering, database, Synthetic biology, novel biosynthetic pathways
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