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Robust Signal Processing in Living Cells

Overview of attention for article published in PLoS Computational Biology, November 2011
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Title
Robust Signal Processing in Living Cells
Published in
PLoS Computational Biology, November 2011
DOI 10.1371/journal.pcbi.1002218
Pubmed ID
Authors

Ralf Steuer, Steffen Waldherr, Victor Sourjik, Markus Kollmann

Abstract

Cellular signaling networks have evolved an astonishing ability to function reliably and with high fidelity in uncertain environments. A crucial prerequisite for the high precision exhibited by many signaling circuits is their ability to keep the concentrations of active signaling compounds within tightly defined bounds, despite strong stochastic fluctuations in copy numbers and other detrimental influences. Based on a simple mathematical formalism, we identify topological organizing principles that facilitate such robust control of intracellular concentrations in the face of multifarious perturbations. Our framework allows us to judge whether a multiple-input-multiple-output reaction network is robust against large perturbations of network parameters and enables the predictive design of perfectly robust synthetic network architectures. Utilizing the Escherichia coli chemotaxis pathway as a hallmark example, we provide experimental evidence that our framework indeed allows us to unravel the topological organization of robust signaling. We demonstrate that the specific organization of the pathway allows the system to maintain global concentration robustness of the diffusible response regulator CheY with respect to several dominant perturbations. Our framework provides a counterpoint to the hypothesis that cellular function relies on an extensive machinery to fine-tune or control intracellular parameters. Rather, we suggest that for a large class of perturbations, there exists an appropriate topology that renders the network output invariant to the respective perturbations.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 138 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 10 7%
United Kingdom 3 2%
Netherlands 2 1%
Germany 2 1%
Australia 1 <1%
Finland 1 <1%
Portugal 1 <1%
Brazil 1 <1%
India 1 <1%
Other 0 0%
Unknown 116 84%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 40 29%
Researcher 36 26%
Student > Master 13 9%
Professor > Associate Professor 11 8%
Professor 6 4%
Other 24 17%
Unknown 8 6%
Readers by discipline Count As %
Agricultural and Biological Sciences 65 47%
Engineering 15 11%
Physics and Astronomy 10 7%
Biochemistry, Genetics and Molecular Biology 9 7%
Computer Science 9 7%
Other 21 15%
Unknown 9 7%