Giorgos Minas -- Efficient simulation, analysis and inference for large oscillatory stochastic systems [ONLINE]
| Dates: | 1 May 2024 |
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| Times: | 13:00 - 14:00 |
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| What is it: | Seminar |
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| Organiser: | Department of Mathematics |
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| Who is it for: | University staff, External researchers, Current University students |
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| Speaker: | Giorgos Minas |
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Join us for this seminar by Giorgos Minas (St Andrews) as part of the North West Seminar Series in Mathematical Biology and Data Sciences
The talk will be hosted by the University of Liverpool and available to watch via zoom. Please contact carl.whitfield@manchester.ac.uk or mdomijan@liverpool.ac.uk for the link, or sign up to the mailing list.
Title: Efficient simulation, analysis and inference for large oscillatory stochastic systems
Abstract: In this talk, we will consider stochastic models and computational algorithms that are used to study the evolution of interacting populations over time. We will consider the methods used to study gene regulation, cell signalling, stem-cell development, but also epidemics of infectious diseases by mechanistic modelling of these interactions. We will focus on two examples: an endogenous biological clock that regulates a roughly 24-hour cycle in almost every single cell of living organisms and a signalling system controlling the immune response to inflammation. First, I will introduce the Markov stochastic processes used in this setting, and then focus on a model described by Stochastic Differential Equations (SDEs) called phase-corrected Linear Noise Approximation (pcLNA). pcLNA takes advantage of the transversal stability of systems that macroscopically present attractive limit cycles to perform long-time accurate yet fast stochastic simulation, even for large systems. We will discuss how to compute the likelihood of time-series data observing the evolution of populations and how to perform sensitivity analysis using pcLNA. We will then explore Bayesian inference and a parallel-tempering Markov Chain Monte Carlo to estimate the parameters of the mechanistic models.
Related papers:
Swallow, Ben, David A. Rand, and Giorgos Minas. "Bayesian inference for stochastic oscillatory systems using the phase-corrected Linear Noise Approximation." arXiv preprint arXiv:2205.05955 (2024).
To subscribe to the mailing list for this event series, please send an e-mail with the phrase “subscribe math-lifesci-seminar” in the message body to listserv@listserv.manchester.ac.uk
Speaker
Giorgos Minas
Role: Lecturer
Organisation: University of St Andrews
Travel and Contact Information
