The biological systems have been investigated by stochastic thermodynamic approach, especially for E. coli sensory adaptation model. Recently, using information geometry and stochastic thermo- dynamics, the relationship between speed on information geometry of transition and thermodynamic cost is investigated in biochemical enzymatic reaction model. Here, we introduce the approach to E. coli sensory adaptation model , and investigated the relationship between adaptation speed and rate of thermodynamic cost change and efficiency of the adaptation  . For increasing external noise level in stimulation, the efficiency decreased, but for external stimulation strength, the efficiency was highly robust . Using this approach, we succeeded to discuss the relationship between speed of adaptation and rate of thermodynamic cost change in E. coli adaptation. Our quantification could be applied to various biological systems.
Biological systems process information under noisy environment. Sensory adaptation model of E. coli is suitable for investigation because of its simplicity. To understand the adaptation processing quantitatively, stochastic thermodynamic approach has been attempted. Information processing can be assumed as state transition of a system that consists of signal transduction molecules using thermodynamic approach, and efficiency can be measured as a thermodynamic cost. Recently, using information geometry and stochastic thermodynamics, a relationship between speed of the transition and the thermodynamic cost has been investigated for a chemical reaction model. Here, we introduce this approach to sensory adaptation model of E. coli, and examined a relationship between adaptation speed and rate of the thermodynamic-cost change, and efficiency of the adaptation speed . For increasing external noise level in stimulation, the efficiency decreased, but the efficiency was highly robust to external stimulation strength. Our quantification method provides a framework to understand the adaptation speed and the thermodynamic cost for various biological systems.
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The biological systems have been investigated by stochastic thermodynamic approach, especially for
Biological systems process information under noisy environment. Sensory adaptation model of
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sensory adaptation model.
is suitable for investigation because of its simplicity. To understand the adaptation processing quantitatively, stochastic thermodynamic approach has been attempted. Information processing can be assumed as state transition of a system that consists of signal transduction molecules using thermodynamic approach, and efficiency can be measured as a thermodynamic cost.
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thermo- dynamics, the
thermodynamics, a
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on information geometry of transition and thermodynamic cost is investigated in biochemical enzymatic
of the transition and the thermodynamic cost has been investigated for a chemical
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the approach to E. coli
this approach to
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, and investigated the
of E. coli, and examined a
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thermodynamic cost change
the thermodynamic-cost change,
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speed
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for external stimulation strength,
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. Using this approach, we succeeded to discuss the relationship between speed of adaptation and rate of thermodynamic cost change in E. coli adaptation. Our quantification could be applied to
to external stimulation strength. Our quantification method provides a framework to understand the adaptation speed and the thermodynamic cost for