Energy consumption and cooperation for optimal sensing
| Autor: | David J. Schwab, Vudtiwat Ngampruetikorn, Greg J. Stephens |
|---|---|
| Přispěvatelé: | LaserLaB - Molecular Biophysics, Physics of Living Systems |
| Jazyk: | angličtina |
| Rok vydání: | 2020 |
| Předmět: |
Computer science
Cells Science Population Biophysics General Physics and Astronomy FOS: Physical sciences Biosensing Techniques Biostatistics Signal-To-Noise Ratio 01 natural sciences Signal Models Biological General Biochemistry Genetics and Molecular Biology Biophysical Phenomena Article 010305 fluids & plasmas SDG 17 - Partnerships for the Goals Control theory 0103 physical sciences Limit (mathematics) Physics - Biological Physics Statistical physics thermodynamics and nonlinear dynamics 010306 general physics education lcsh:Science education.field_of_study Multidisciplinary Noise (signal processing) General Chemistry Energy consumption Mutual information Function (mathematics) Chemoreceptor Cells Gene Expression Regulation Biological Physics (physics.bio-ph) lcsh:Q Energy Metabolism Biological physics Energy (signal processing) Signal Transduction |
| Zdroj: | Nature Communications, 11(1):975, 1-8. Nature Publishing Group Nature Communications, Vol 11, Iss 1, Pp 1-8 (2020) Ngampruetikorn, V, Schwab, D J & Stephens, G J 2020, ' Energy consumption and cooperation for optimal sensing ', Nature Communications, vol. 11, no. 1, 975, pp. 1-8 . https://doi.org/10.1038/s41467-020-14806-y Nature Communications |
| ISSN: | 2041-1723 |
| DOI: | 10.1038/s41467-020-14806-y |
| Popis: | The reliable detection of environmental molecules in the presence of noise is an important cellular function, yet the underlying computational mechanisms are not well understood. We introduce a model of two interacting sensors which allows for the principled exploration of signal statistics, cooperation strategies and the role of energy consumption in optimal sensing, quantified through the mutual information between the signal and the sensors. Here we report that in general the optimal sensing strategy depends both on the noise level and the statistics of the signals. For joint, correlated signals, energy consuming (nonequilibrium), asymmetric couplings result in maximum information gain in the low-noise, high-signal-correlation limit. Surprisingly we also find that energy consumption is not always required for optimal sensing. We generalise our model to incorporate time integration of the sensor state by a population of readout molecules, and demonstrate that sensor interaction and energy consumption remain important for optimal sensing. Comment: 9 pages, 5 figures, Forthcoming in Nature Communications |
| Databáze: | OpenAIRE |
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