ArticleNature communications2022
Frequency spectra and the color of cellular noise.
Article in Nature communications, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
5 citing papers in PubMed.
- Monitoring Glutathione Content of the Endoplasmic Reticulum under Scrap Leather-Induced Endoplasmic Reticulum Stress via an Endoplasmic Reticulum-Targeted Two-Photon Fluorescent Probe.Analytical chemistry · 2024Article
- Advanced methods for gene network identification and noise decomposition from single-cell data.Nature communications · 2024Article
- Frequency spectra and the color of cellular noise.Nature communications · 2022Article
- A hierarchy of biomolecular proportional-integral-derivative feedback controllers for robust perfect adaptation and dynamic performance.Nature communications · 2022Article
- Rapid prototyping and design of cybergenetic single-cell controllers.Nature communications · 2021Article
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Authors and funding
2 authors.
Funding
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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.
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