Metabolic Systems Biology: A Constraint-Based Approach

Bibliome The collection of primary literature, review lit19 erature and textbooks on a particular topic. 20 Biochemically, genetically and genomically (BiGG) 21 structured reconstruction A structured genome-scale 22 metabolic network reconstruction which incorpo23 rates knowledge about the genomic, proteomic, and 24 biochemical components, including relationships be25 tween each component in a particular organism or 26 cell (See Sect. “Reconstructions, Knowledge Bases, and 27 Models”). 28 Biomass function A pseudo-reaction representing the 29 stoichiometric consumption of metabolites necessary 30 for cellular growth (i. e., to produce biomass). When 31 this pseudo-reaction is placed in a model, a flux 32 through it represents the in silico growth rate of the 33 organism or population (See Sect. “Constraint-Based 34 Methods of Analysis”). 35 Constraint-Based reconstruction and analysis (COBRA) 36 A set of approaches for constructing manually curated, 37 stoichiometric network reconstructions and analyzing 38 the resulting models by applying equality and inequal39 ity constraints and computing functional states. In 40 general, mass conservation and thermodynamics (for 41 directionality) are the fundamental constraints. Addi42 tional constraints reflecting experimental conditions 43 and other biological constraints (such as regulatory 44 states) can be applied. The analysis approaches gener45 ally fall into two classes: biased and unbiased methods. 46 Biased methods involve the application of various op47 timization approaches which require the definition 48 of an objective function. Unbiased methods do not 49 require an objective function (See Sect. “Constraint50 Based Modeling”). 51 Convex space A multi-dimensional space in which 52 a straight line can be drawn from any two, without 53 leaving the space (see Sect. “Constraint-Based Meth54 ods of Analysis”). 55 Extreme pathways (ExPa) analysis An approach for cal56 culating a unique, linearly independent, but biochem57 ically feasible reaction basis that can describe all pos58 sible steady state flux combinations in a biochemi59 cal network. ExPas are closely related to Elementary 60 Modes (See Sect. “Constraint-Based Methods of Anal61 ysis”). 62 Flux-balance analysis (FBA) The formalism in which 63 a metabolic network is framed as a linear program64 ming optimization problem. The principal constraints 65 in FBA are those imposed by steady state mass con66 servation of metabolites in the system (See Sect. “Con67 straint-Based Methods of Analysis”). 68 Gene-protein-reaction association (GPR) A mathemat69 ical representation of the relationships between gene 70 loci, gene transcripts, protein sub-units, enzymes, and 71 reactions using logical relationships (and/or) (See 72 Sect. “Reconstructions, Knowledge Bases, and Mod73 els”). 74 Genome-scale The characterization of a cellular func75 tion/system on its genome scale, i. e., incorpora76 tion/consideration of all known associated compo77 nents encoded in the organism’s genome. 78 Isocline A line in a phenotypic phase plane diagram, 79 along which the ratio between the shadow prices for 80 two metabolites is fixed (See Sect. “Constraint-Based 81 Methods of Analysis”). 82 Knowledge base A specific type of reconstruction which 83 also accounts for the following information: molecular 84 formulae, subsystem assignments, GPRs, references to 85 primary and review literature, and additional pertinent 86 notes (See Sect. “Reconstructions, Knowledge Bases, 87 and Models”). 88 Line of optimality The isocline in a phenotypic phase 89 plane diagram that achieves the highest value of the ob90 jective in the phase plane (See Sect. “Constraint-Based 91 Methods of Analysis”). 92 Linear programming problem A class of optimization 93 problems in which a linear objective function is max94 imized or minimized subject to linear equality and 95