FM-Sim: A Hybrid Protocol Simulator of Fluorescence Microscopy Neuroscience Assays with Integrated Bayesian Inference
We present FM-Sim, a domain-specific simulator for defining and simulating fluorescence microscopy assays. Experimental protocols as performed in vitro may be defined in the simulator. The defined protocols then interact with a computational model of presynaptic behaviour in rodent central nervous system neurons, allowing simulation of fluorescent responses to varying stimuli. Rate parameters of the model may be obtained using Bayesian inference functions integrated into the simulator, given experimental fluorescence observations of the protocol performed in vitro as training data. These trained protocols allow for predictive in silico modelling of potential experimental outcomes prior to time-consuming and expensive in vitro studies.
KeywordsSynaptic Vesicle Nerve Terminal Extracellular Medium Marginal Likelihood Sequential Monte Carlo
Thanks to the members of the Cousin group, in particular Sarah Gordon, for helpful discussions, and provision of experimental data. Thanks also to the reviewers of this paper for their helpful comments and suggestions.
This work was supported in part by grants EP/F500385/1 and BB/F529254/1 for the University of Edinburgh School of Informatics Doctoral Training Centre in Neuroinformatics and Computational Neuroscience (www.anc.ac.uk/dtc) from the UK Engineering and Physical Sciences Research Council (EPSRC), UK Biotechnology and Biological Sciences Research Council (BBSRC), and the UK Medical Research Council (MRC). The work has made use of resources provided by the Edinburgh Compute and Data Facility (ECDF; www.ecdf.ed.ac.uk), which has support from the eDIKT initiative (www.edikt.org.uk).
Stephen Gilmore is supported by the BBSRC SysMIC grant, BB/I014713/1.
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