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An endergonic reaction (such as photosynthesis) is a reaction that requires energy to be driven. Endergonic means "absorbing energy in the form of work." The activation energy for the reaction is typically larger than the overall energy of the exergonic reaction (1). Endergonic reactions are nonspontaneous.
The ∆G° can be written as a function of change in enthalpy (∆H°) and change in entropy (∆S°) as ∆G°= ∆H° – T∆S°. Practically, enthalpies, not free energy, are used to determine whether a reaction is favorable or unfavorable, because ∆ H ° is easier to measure and T ∆ S ° is usually too small to be of any significance ...
The energy released by this highly exergonic oxidation reaction drives the endergonic second reaction (ΔG°'=+50 kJ/mol (+12kcal/mol)), in which a molecule of inorganic phosphate is transferred to the GAP intermediate to form a product with high phosphoryl-transfer potential: 1,3-bisphosphoglycerate (1,3-BPG).
The reaction quotient (Q r) is the ratio of the chemical activity (a i) of the reduced form (the reductant, a Red) to the activity of the oxidized form (the oxidant, a ox). It is equal to the ratio of their concentrations (C i) only if the system is sufficiently diluted and the activity coefficients (γ i) are close to unity (a i = γ i C i):
In biology, taxonomic rank (which some authors prefer to call nomenclatural rank [1] because ranking is part of nomenclature rather than taxonomy proper, according to some definitions of these terms) is the relative or absolute level of a group of organisms (a taxon) in a hierarchy that reflects evolutionary
Its symbol is Δ f G˚. All elements in their standard states (diatomic oxygen gas, graphite, etc.) have standard Gibbs free energy change of formation equal to zero, as there is no change involved. Δ f G = Δ f G˚ + RT ln Q f, where Q f is the reaction quotient. At equilibrium, Δ f G = 0, and Q f = K, so the equation becomes Δ f G˚ = − ...
Of these ranks, domains are the most general level of categorization. Presently, scientists classify all life into just three domains, Eukaryotes, Bacteria and Archaea. [2] Bacterial taxonomy is the classification of strains within the domain Bacteria into hierarchies of similarity.
In statistics, the phi coefficient (or mean square contingency coefficient and denoted by φ or r φ) is a measure of association for two binary variables.. In machine learning, it is known as the Matthews correlation coefficient (MCC) and used as a measure of the quality of binary (two-class) classifications, introduced by biochemist Brian W. Matthews in 1975.