A Bayesian approach to modelling heterogeneous calcium responses in cell populations
Calcium responses have been observed as spikes of the whole-cell calcium concentration in numerous cell types and are essential for translating extracellular stimuli into cellular responses. While there are several suggestions for how this encoding is achieved, we still lack a comprehensive theory....
| Main Authors: | , , , , |
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| Format: | Article |
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Public Library of Science
2017
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| Online Access: | https://eprints.nottingham.ac.uk/47387/ |
| _version_ | 1848797533390766080 |
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| author | Tilunaite, Agne Croft, Wayne Russell, Noah A. Bellamy, Tomas C. Thul, Ruediger |
| author_facet | Tilunaite, Agne Croft, Wayne Russell, Noah A. Bellamy, Tomas C. Thul, Ruediger |
| author_sort | Tilunaite, Agne |
| building | Nottingham Research Data Repository |
| collection | Online Access |
| description | Calcium responses have been observed as spikes of the whole-cell calcium concentration in numerous cell types and are essential for translating extracellular stimuli into cellular responses. While there are several suggestions for how this encoding is achieved, we still lack a comprehensive theory. To achieve this goal it is necessary to reliably predict the temporal evolution of calcium spike sequences for a given stimulus. Here, we propose a modelling framework that allows us to quantitatively describe the timing of calcium spikes. Using a Bayesian approach, we show that Gaussian processes model calcium spike rates with high fidelity and perform better than standard tools such as peri-stimulus time histograms and kernel smoothing. We employ our modelling concept to analyse calcium spike sequences from dynamically-stimulated HEK293T cells. Under these conditions, different cells often experience diverse stimuli time courses, which is a situation likely to occur in vivo. This single cell variability and the concomitant small number of calcium spikes per cell pose a significant modelling challenge, but we demonstrate that Gaussian processes can successfully describe calcium spike rates in these circumstances. Our results therefore pave the way towards a statistical description of heterogeneous calcium oscillations in a dynamic environment |
| first_indexed | 2025-11-14T20:05:23Z |
| format | Article |
| id | nottingham-47387 |
| institution | University of Nottingham Malaysia Campus |
| institution_category | Local University |
| last_indexed | 2025-11-14T20:05:23Z |
| publishDate | 2017 |
| publisher | Public Library of Science |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | nottingham-473872020-05-04T19:11:10Z https://eprints.nottingham.ac.uk/47387/ A Bayesian approach to modelling heterogeneous calcium responses in cell populations Tilunaite, Agne Croft, Wayne Russell, Noah A. Bellamy, Tomas C. Thul, Ruediger Calcium responses have been observed as spikes of the whole-cell calcium concentration in numerous cell types and are essential for translating extracellular stimuli into cellular responses. While there are several suggestions for how this encoding is achieved, we still lack a comprehensive theory. To achieve this goal it is necessary to reliably predict the temporal evolution of calcium spike sequences for a given stimulus. Here, we propose a modelling framework that allows us to quantitatively describe the timing of calcium spikes. Using a Bayesian approach, we show that Gaussian processes model calcium spike rates with high fidelity and perform better than standard tools such as peri-stimulus time histograms and kernel smoothing. We employ our modelling concept to analyse calcium spike sequences from dynamically-stimulated HEK293T cells. Under these conditions, different cells often experience diverse stimuli time courses, which is a situation likely to occur in vivo. This single cell variability and the concomitant small number of calcium spikes per cell pose a significant modelling challenge, but we demonstrate that Gaussian processes can successfully describe calcium spike rates in these circumstances. Our results therefore pave the way towards a statistical description of heterogeneous calcium oscillations in a dynamic environment Public Library of Science 2017-10-06 Article PeerReviewed Tilunaite, Agne, Croft, Wayne, Russell, Noah A., Bellamy, Tomas C. and Thul, Ruediger (2017) A Bayesian approach to modelling heterogeneous calcium responses in cell populations. PLoS Computational Biology, 13 (10). e1005794.. ISSN 1553-734X http://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1005794 doi:10.1371/journal.pcbi.1005794 doi:10.1371/journal.pcbi.1005794 |
| spellingShingle | Tilunaite, Agne Croft, Wayne Russell, Noah A. Bellamy, Tomas C. Thul, Ruediger A Bayesian approach to modelling heterogeneous calcium responses in cell populations |
| title | A Bayesian approach to modelling heterogeneous calcium responses in cell populations |
| title_full | A Bayesian approach to modelling heterogeneous calcium responses in cell populations |
| title_fullStr | A Bayesian approach to modelling heterogeneous calcium responses in cell populations |
| title_full_unstemmed | A Bayesian approach to modelling heterogeneous calcium responses in cell populations |
| title_short | A Bayesian approach to modelling heterogeneous calcium responses in cell populations |
| title_sort | bayesian approach to modelling heterogeneous calcium responses in cell populations |
| url | https://eprints.nottingham.ac.uk/47387/ https://eprints.nottingham.ac.uk/47387/ https://eprints.nottingham.ac.uk/47387/ |