What is flux balance analysis?

By Jeffrey D. Orth, Ines Thiele, Bernhard O. Palsson. Nature Biotechnology, 2010

3,491 citations recorded by the source corpus.

Flux balance analysis is a mathematical approach for analyzing the flow of metabolites through a metabolic network. This primer covers the theoretical basis of the approach, several practical examples and a software toolbox for performing the calculations.

Subfields: Control and Systems Engineering, Molecular Biology

View Paper: https://www.semanticscholar.org/paper/e0fb2512d8b88860b4cd1a28c18024b76c1b97d1

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Citations in the corpus

Basic and applied uses of genome-scale metabolic network reconstructions of Escherichia coli (2013, background): “Genome-scale models (GEMs) are a structured format of such a knowledge base that can be used to perform computational and quantitative queries to answer various questions about the capabilities of organisms and their likely phenotypic states (Palsson, 2006; Orth et al , 2010).”
Inverse statistical problems: from the inverse Ising problem to data science (2017, background): “An example where such a network optimizes a specific global quantity is flux-balance analysis [166], which models the flow of metabolites through a metabolic network.”
Using Genome-Scale Models to Predict Biological Capabilities (2015, neutral): “It is a mathematical approach for analyzing the ﬂow of metabolites through a metabolic network (Orth et al., 2010).”
Translation of Genotype to Phenotype by a Hierarchy of Cell Subsystems (2016, background): “, see (Cahan et al., 2014; Carrera et al., 2014; Deutscher et al., 2006; Karr et al., 2012; Lerman et al., 2012; Machado et al., 2011; O’Brien et al., 2013; Orth et al., 2010; Segrè et al., 2005; Szappanos et al., 2011; Szczurek et al., 2009; Takahashi et al., 2003; Tomita et al., 1999) have been dr”
Constraint-based models predict metabolic and associated cellular functions (2014, methodology): “The standard approach of flux-balance analysis 104 either maximizes or minimizes the flux of a user-defined reaction (that is, the objective function) using linear programming (shown by the green circle).”
Recon3D: A Resource Enabling A Three-Dimensional View of Gene Variation in Human Metabolism (2018, positive): “This data was used to guide and inform genome-scale constraint-based modeling analyses 42,43 to identify the metabolic pathways most perturbed in a given condition (Supplementary Figure 15).”
Metabolic dependencies drive species co-occurrence in diverse microbial communities (2015, background): “the environment, these models can be used to simulate growth and metabolite production capabilities of corresponding species (39).”
Systems Biology and Multi-Omics Integration: Viewpoints from the Metabolomics Research Community (2019, background): “These modeling systems may incorporate dynamic/kinetic models that solve systems of differential, or partial differential equations [55], agent-based kinetic models [56], or Petri-Net models [57] or they may involve steady state models, such as flux-balance models [58].”
Efficient searching and annotation of metabolic networks using chemical similarity (2015, methodology): “For this task, numerous in silico utilities, such as metabolic flux analysis (Orth et al. , 2010), have been developed to optimize existing pathways, engineer novel pathways and identify drug targets by simulating the effect of remodeling the underlying metabolic network and analyzing its topology…”
Constraining the metabolic genotype-phenotype relationship using a phylogeny of in silico methods (2012, methodology): “Using linear programing, an objective function (for example, the biomass objective function) is optimized subject to the constraints imposed by the metabolic network and metabolite uptake rates 10,11,40 .”