ArticleInterface focus2014
It is not the parts, but how they interact that determines the behaviour of circadian rhythms across scales and organisms.
Article in Interface focus, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.
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Who cites it
15 citing papers in PubMed, 31 citations in OpenAlex.
- The inferred functional connectome underlying circadian synchronization in the mouse suprachiasmatic nucleus.Proceedings of the National Academy of Sciences of the United States of America · 2025Article
- The Functional Connectome Mediating Circadian Synchrony in the Suprachiasmatic Nucleus.bioRxiv : the preprint server for biology · 2024Article
- A new phase model of the spatiotemporal relationships between three circadian oscillators in the brainstem.Scientific reports · 2023Article
- A Phenomenological Mouse Circadian Pacemaker Model.Journal of biological rhythms · 2022Article
- Targeted modification of the Per2 clock gene alters circadian function in mPer2luciferase (mPer2Luc) mice.PLoS computational biology · 2021Article
- Mathematical modeling of circadian rhythms.Wiley interdisciplinary reviews. Systems biology and medicine · 2019Review
- Applying evolutionary genetics to developmental toxicology and risk assessment.Reproductive toxicology (Elmsford, N.Y.) · 2017Review
- Computational modeling of the cell-autonomous mammalian circadian oscillator.BMC systems biology · 2017Article
- Hypothesis driven single cell dual oscillator mathematical model of circadian rhythms.PloS one · 2017Article
- Protein sequestration versus Hill-type repression in circadian clock models.IET systems biology · 2016Review
- From global to local: exploring the relationship between parameters and behaviors in models of electrical excitability.Journal of computational neuroscience · 2016Article
- Functional network inference of the suprachiasmatic nucleus.Proceedings of the National Academy of Sciences of the United States of America · 2016Article
- Asymmetry in Signal Oscillations Contributes to Efficiency of Periodic Systems.Critical reviews in biomedical engineering · 2016Article
- Distinct roles for GABA across multiple timescales in mammalian circadian timekeeping.Proceedings of the National Academy of Sciences of the United States of America · 2015Article
- GABA-mediated repulsive coupling between circadian clock neurons in the SCN encodes seasonal time.Proceedings of the National Academy of Sciences of the United States of America · 2015Article
Corrections and comments
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Authors and funding
4 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Biological rhythms, generated by feedback loops containing interacting genes, proteins and/or cells, time physiological processes in many organisms. While many of the components of the systems that generate biological rhythms have been identified, much less is known about the details of their interactions. Using examples from the circadian (daily) clock in three organisms, Neurospora, Drosophila and mouse, we show, with mathematical models of varying complexity, how interactions among (i) promoter sites, (ii) proteins forming complexes, and (iii) cells can have a drastic effect on timekeeping. Inspired by the identification of many transcription factors, for example as involved in the Neurospora circadian clock, that can both activate and repress, we show how these multiple actions can cause complex oscillatory patterns in a transcription-translation feedback loop (TTFL). Inspired by the timekeeping complex formed by the NMO-PER-TIM-SGG complex that regulates the negative TTFL in the Drosophila circadian clock, we show how the mechanism of complex formation can determine the prevalence of oscillations in a TTFL. Finally, we note that most mathematical models of intracellular clocks model a single cell, but compare with experimental data from collections of cells. We find that refitting the most detailed model of the mammalian circadian clock, so that the coupling between cells matches experimental data, yields different dynamics and makes an interesting prediction that also matches experimental data: individual cells are bistable, and network coupling removes this bistability and causes the network to be more robust to external perturbations. Taken together, we propose that the interactions between components in biological timekeeping systems are carefully tuned towards proper function. We also show how timekeeping can be controlled by novel mechanisms at different levels of organization.
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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.