ArticlePLoS computational biology2017
Identifying stochastic oscillations in single-cell live imaging time series using Gaussian processes.
Article in PLoS computational biology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.
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Who cites it
20 citing papers in PubMed, 39 citations in OpenAlex.
- Oscillatory co-expression of HES1 and HES5 enables a hybrid state in a cross-repressive transcription factor regulatory motif.Development (Cambridge, England) · 2026Article
- Are physiological oscillations physiological?The Journal of physiology · 2026Review
- HES1 oscillations are required for cell cycle reentry in oestrogen receptor-positive breast cancer cells.Proceedings of the National Academy of Sciences of the United States of America · 2026Article
- GPMelt: A hierarchical Gaussian process framework to explore the dark meltome of thermal proteome profiling experiments.PLoS computational biology · 2024Article
- Cell coupling compensates for changes in single-cell Her6 dynamics and provides phenotypic robustness.Development (Cambridge, England) · 2024Article
- An improved rhythmicity analysis method using Gaussian Processes detects cell-density dependent circadian oscillations in stem cells.Bioinformatics (Oxford, England) · 2023Article
- An improved rhythmicity analysis method using Gaussian Processes detects cell-density dependent circadian oscillations in stem cells.bioRxiv : the preprint server for biology · 2023Article
- Temporal control of the integrated stress response by a stochastic molecular switch.Science advances · 2022Article
- Differential phase register of Hes1 oscillations with mitoses underlies cell-cycle heterogeneity in ERProceedings of the National Academy of Sciences of the United States of America · 2021Article
- A digital health platform for assisting the diagnosis and monitoring of COVID-19 progression: An adjuvant approach for augmenting the antiviral response and mitigating the immune-mediated target organ damage.Biomedicine & pharmacotherapy = Biomedecine & pharmacotherapie · 2021Article
- HES1 protein oscillations are necessary for neural stem cells to exit from quiescence.iScience · 2021Article
- A functionally divergent intrinsically disordered region underlying the conservation of stochastic signaling.PLoS genetics · 2021Article
- Inferring kinetic parameters of oscillatory gene regulation from single cell time-series data.Journal of the Royal Society, Interface · 2021Article
- Inference of dominant modes for linear stochastic processes.Royal Society open science · 2021Article
- Computationally enhanced quantitative phase microscopy reveals autonomous oscillations in mammalian cell growth.Proceedings of the National Academy of Sciences of the United States of America · 2020Article
- Dynamic properties of noise and Her6 levels are optimized by miR-9, allowing the decoding of the Her6 oscillator.The EMBO journal · 2020Article
- Order Through Disorder: The Characteristic Variability of Systems.Frontiers in cell and developmental biology · 2020Review
- Intrinsic noise, Delta-Notch signalling and delayed reactions promote sustained, coherent, synchronized oscillations in the presomitic mesoderm.Journal of the Royal Society, Interface · 2019Article
- Quantitative single-cell live imaging links HES5 dynamics with cell-state and fate in murine neurogenesis.Nature communications · 2019Article
- A Noisy Analog-to-Digital Converter Connects Cytosolic Calcium Bursts to Transcription Factor Nuclear Localization Pulses in Yeast.G3 (Bethesda, Md.) · 2019Article
Corrections and comments
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Authors and funding
4 authors at 1 institution in 1 country.
Funding
Abstract
Multiple biological processes are driven by oscillatory gene expression at different time scales. Pulsatile dynamics are thought to be widespread, and single-cell live imaging of gene expression has lead to a surge of dynamic, possibly oscillatory, data for different gene networks. However, the regulation of gene expression at the level of an individual cell involves reactions between finite numbers of molecules, and this can result in inherent randomness in expression dynamics, which blurs the boundaries between aperiodic fluctuations and noisy oscillators. This underlies a new challenge to the experimentalist because neither intuition nor pre-existing methods work well for identifying oscillatory activity in noisy biological time series. Thus, there is an acute need for an objective statistical method for classifying whether an experimentally derived noisy time series is periodic. Here, we present a new data analysis method that combines mechanistic stochastic modelling with the powerful methods of non-parametric regression with Gaussian processes. Our method can distinguish oscillatory gene expression from random fluctuations of non-oscillatory expression in single-cell time series, despite peak-to-peak variability in period and amplitude of single-cell oscillations. We show that our method outperforms the Lomb-Scargle periodogram in successfully classifying cells as oscillatory or non-oscillatory in data simulated from a simple genetic oscillator model and in experimental data. Analysis of bioluminescent live-cell imaging shows a significantly greater number of oscillatory cells when luciferase is driven by a Hes1 promoter (10/19), which has previously been reported to oscillate, than the constitutive MoMuLV 5' LTR (MMLV) promoter (0/25). The method can be applied to data from any gene network to both quantify the proportion of oscillating cells within a population and to measure the period and quality of oscillations. It is publicly available as a MATLAB package.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.