Publication | Open Access
Thermodynamic Uncertainty Relation for Biomolecular Processes
934
Citations
27
References
2015
Year
EngineeringMolecular BiologyUncertainty εStochastic AnalysisUncertainty ModelingStochastic SimulationThermodynamic ModellingSteady StateMolecular ThermodynamicsUncertainty QuantificationStochastic ProcessesMolecular MotorsThermodynamicsBiophysicsStochastic SystemProbability TheoryThermodynamic Uncertainty RelationBiomolecular EngineeringStochastic ModelingProcess DynamicsEntropyUncertainty PrincipleMarkov KernelSystems Biology
Biomolecular systems like molecular motors or pumps, transcription and translation machinery, and other enzymatic reactions, can be described as Markov processes on a suitable network. We show quite generally that, in a steady state, the dispersion of observables, like the number of consumed or produced molecules or the number of steps of a motor, is constrained by the thermodynamic cost of generating it. An uncertainty ε requires at least a cost of 2k(B)T/ε2 independent of the time required to generate the output.
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