cellular solution to an information-processing problem

Signaling receptors on the cell surface are mobile and have evolved to efficiently sense and process mechanical or chemical information. We pose the problem of identifying the optimal strategy for placing a collection of distributed and mobile sensors to faithfully estimate a signal that varies in s...

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Bibliographic Details
Published in:Proceedings of the National Academy of Sciences - PNAS 2014-08, Vol.111 (34), p.12402-12407
Main Authors: Iyengar, Garud, Rao, Madan
Format: Article
Language:English
Subjects:
Architecture
Automatic Data Processing - methods
Biological Sciences
Cell membranes
Cell surface receptors
Cells
Computational Biology - methods
Information processing
Information Theory
Membrane proteins
Models, Biological
Optimal solutions
Physical Sciences
Proteins
Receptors
Receptors, Cell Surface - metabolism
Sensors
Signal noise
Signal Transduction
Stochastic models
Stochastic Processes
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Summary:Signaling receptors on the cell surface are mobile and have evolved to efficiently sense and process mechanical or chemical information. We pose the problem of identifying the optimal strategy for placing a collection of distributed and mobile sensors to faithfully estimate a signal that varies in space and time. The optimal strategy has to balance two opposing objectives: the need to locally assemble sensors to reduce estimation noise and the need to spread them to reduce spatial error. This results in a phase transition in the space of strategies as a function of sensor density and efficiency. We show that these optimal strategies have been arrived at multiple times in diverse cell biology contexts, including the stationary lattice architecture of receptors on the bacterial cell surface and the active clustering of cell-surface signaling receptors in metazoan cells.
ISSN:0027-8424
1091-6490
DOI:10.1073/pnas.1406608111