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Updated: Mar 3, 2026

A Web Tool for Generating High Quality Machine-readable Biological Pathways
Published on: February 8, 2017
ChloroKB: A Web Application for the Integration of Knowledge Related to Chloroplast Metabolic Network
Pauline Gloaguen1, Sylvain Bournais1, Claude Alban1
1Laboratoire de Biologie à Grande Echelle (BGE), CEA, INSERM, BIG, Université Grenoble-Alpes, 38000, Grenoble, France (P.G., S.B., M.T., M.F., C.B, Y.V.); Laboratoire de Physiologie Cellulaire et Végétale (LPCV), CNRS, CEA, INRA, BIG, Université Grenoble-Alpes, 38000, Grenoble, France (C.A., S.R., D.S.-B., M.M., M.K., N.R., G.C.).
Abstract:
Higher plants, as autotrophic organisms, are effective sources of molecules. They hold great promise for metabolic engineering, but the behavior of plant metabolism at the network level is still incompletely described. Although structural models (stoichiometry matrices) and pathway databases are extremely useful, they cannot describe the complexity of the metabolic context, and new tools are required to visually represent integrated biocurated knowledge for use by both humans and computers. Here, we describe ChloroKB, a Web application (http://chlorokb.fr/) for visual exploration and analysis of the Arabidopsis (Arabidopsis thaliana) metabolic network in the chloroplast and related cellular pathways. The network was manually reconstructed through extensive biocuration to provide transparent traceability of experimental data. Proteins and metabolites were placed in their biological context (spatial distribution within cells, connectivity in the network, participation in supramolecular complexes, and regulatory interactions) using CellDesigner software. The network contains 1,147 reviewed proteins (559 localized exclusively in plastids, 68 in at least one additional compartment, and 520 outside the plastid), 122 proteins awaiting biochemical/genetic characterization, and 228 proteins for which genes have not yet been identified. The visual presentation is intuitive and browsing is fluid, providing instant access to the graphical representation of integrated processes and to a wealth of refined qualitative and quantitative data. ChloroKB will be a significant support for structural and quantitative kinetic modeling, for biological reasoning, when comparing novel data with established knowledge, for computer analyses, and for educational purposes. ChloroKB will be enhanced by continuous updates following contributions from plant researchers.
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