ArticleNature protocols2011
Quantitative prediction of cellular metabolism with constraint-based models: the COBRA Toolbox v2.0.
Article in Nature protocols, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 620 papers.
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Who cites it
620 citing papers in PubMed.
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- hiPSCGEM01: A Genome-Scale Metabolic Model for Fibroblast-Derived Human iPSCs.Bioengineering (Basel, Switzerland) · 2025Article
- Investigating Lipid and Energy Dyshomeostasis Induced by Per- and Polyfluoroalkyl Substances (PFAS) Congeners in Mouse Model Using Systems Biology Approaches.Metabolites · 2025Article
- The FBA solution space kernel: introduction and illustrative examples.BMC bioinformatics · 2025Article
- Deep Learning of Cellular Metabolic Flux Distributions Predicts Lifespan.bioRxiv : the preprint server for biology · 2025Article
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- Inverse-Vaccines for Rheumatoid Arthritis Re-establish Metabolic and Immunological Homeostasis in Joint Tissues.Advanced healthcare materials · 2025Article
- Physiology-informed use of Cupriavidus necator in biomanufacturing: a review of advances and challenges.Microbial cell factories · 2025Review
- Boolean matrix logic programming for active learning of gene functions in genome-scale metabolic network models.Machine learning · 2025Article
- Strategy for Optimizing Vitamin B12 Production inMetabolites · 2024Article
560 more citing papers are in PubMed but not listed here.
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Authors and funding
13 authors.
Funding
Abstract
Over the past decade, a growing community of researchers has emerged around the use of constraint-based reconstruction and analysis (COBRA) methods to simulate, analyze and predict a variety of metabolic phenotypes using genome-scale models. The COBRA Toolbox, a MATLAB package for implementing COBRA methods, was presented earlier. Here we present a substantial update of this in silico toolbox. Version 2.0 of the COBRA Toolbox expands the scope of computations by including in silico analysis methods developed since its original release. New functions include (i) network gap filling, (ii) (13)C analysis, (iii) metabolic engineering, (iv) omics-guided analysis and (v) visualization. As with the first version, the COBRA Toolbox reads and writes systems biology markup language-formatted models. In version 2.0, we improved performance, usability and the level of documentation. A suite of test scripts can now be used to learn the core functionality of the toolbox and validate results. This toolbox lowers the barrier of entry to use powerful COBRA methods.
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