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Frequency spectra and the color of cellular noise

Author

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  • Ankit Gupta

    (ETH Zürich)

  • Mustafa Khammash

    (ETH Zürich)

Abstract

The invention of the Fourier integral in the 19th century laid the foundation for modern spectral analysis methods. This integral decomposes a temporal signal into its frequency components, providing deep insights into its generating process. While this idea has precipitated several scientific and technological advances, its impact has been fairly limited in cell biology, largely due to the difficulties in connecting the underlying noisy intracellular networks to the frequency content of observed single-cell trajectories. Here we develop a spectral theory and computational methodologies tailored specifically to the computation and analysis of frequency spectra of noisy intracellular networks. Specifically, we develop a method to compute the frequency spectrum for general nonlinear networks, and for linear networks we present a decomposition that expresses the frequency spectrum in terms of its sources. Several examples are presented to illustrate how our results provide frequency-based methods for the design and analysis of noisy intracellular networks.

Suggested Citation

  • Ankit Gupta & Mustafa Khammash, 2022. "Frequency spectra and the color of cellular noise," Nature Communications, Nature, vol. 13(1), pages 1-18, December.
    • Handle: RePEc:nat:natcom:v:13:y:2022:i:1:d:10.1038_s41467-022-31263-x
    DOI: 10.1038/s41467-022-31263-x
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    References listed on IDEAS

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    Cited by:

    1. Zhou Fang & Ankit Gupta & Sant Kumar & Mustafa Khammash, 2024. "Advanced methods for gene network identification and noise decomposition from single-cell data," Nature Communications, Nature, vol. 15(1), pages 1-19, December.

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