Scalable inference of heterogeneous reaction kinetics from pooled single-cell recordings.

Details

Serval ID
serval:BIB_68F8FB0396B8
Type
Article: article from journal or magazin.
Collection
Publications
Institution
Title
Scalable inference of heterogeneous reaction kinetics from pooled single-cell recordings.
Journal
Nature Methods
Author(s)
Zechner C., Unger M., Pelet S., Peter M., Koeppl H.
ISSN
1548-7105 (Electronic)
ISSN-L
1548-7091
Publication state
Published
Issued date
2014
Peer-reviewed
Oui
Volume
11
Number
2
Pages
197-202
Language
english
Notes
Publication types: Journal Article ; PDF: Article
Abstract
Mathematical methods combined with measurements of single-cell dynamics provide a means to reconstruct intracellular processes that are only partly or indirectly accessible experimentally. To obtain reliable reconstructions, the pooling of measurements from several cells of a clonal population is mandatory. However, cell-to-cell variability originating from diverse sources poses computational challenges for such process reconstruction. We introduce a scalable Bayesian inference framework that properly accounts for population heterogeneity. The method allows inference of inaccessible molecular states and kinetic parameters; computation of Bayes factors for model selection; and dissection of intrinsic, extrinsic and technical noise. We show how additional single-cell readouts such as morphological features can be included in the analysis. We use the method to reconstruct the expression dynamics of a gene under an inducible promoter in yeast from time-lapse microscopy data.
Pubmed
Web of science
Create date
21/03/2014 18:54
Last modification date
20/08/2019 14:24
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