Description

Many problems in science and technology, involving understanding, forecasting and control of physical systems, are addressed by the analysis of computer simulators for the systems. For example climate simulators are used to analyse climate. Before we can use the simulator, say to forecast future outcomes, we often need to tune the simulator input parameters so that the outputs match historical data up to error tolerances.

The process of searching for all input parameter choices which give acceptable matches to observed data is termed history matching, a method that has been successfully applied across a wide variety of scientific areas including the analysis of climate models, galaxy formation simulations, oil reservoirs and models of systems biology.

As the simulator for a complex physical system is often slow to evaluate, for many calculations such as history matching we need to replace it by a Bayesian Emulator: a Bayesian statistical construct that mimics the simulator but which is often several orders of magnitude faster to evaluate.

This project is an exploration of the techniques involved in the above processes, and specifically their application to various models of gene networks in systems biology.

Students will learn how to construct Bayesian emulators, history match complex systems biology models and extend these results to other areas such as the design of future experiments.

Prerequisites

Resources

For an introduction to History Matching as applied to a complex model of Galaxy Formation see our paper entitled "Galaxy Formation: Bayesian History Matching for the Observable Universe" which can be found at Statistical Science Volume 29, No 1.

An excellent web-site which describes (in sometimes overwhelming detail!) the types of analyses which this project gives an introduction to is:

The MUCM Web-site

This is the web-site for the Managing Uncertainty in Complex Models (MUCM) project, a consortium in which we were involved, (with the Universities of Sheffield, Aston, LSE and Southampton). There are an enormous number of links to follow at this site. One in particular, which gives an introduction to emulation, is:

O'Hagan, A. (2006). Bayesian analysis of computer code outputs: a tutorial. Reliability Engineering and System Safety 91, 1290–1300.

See also the MUCM toolkit for a detailed list of emulation and History Matching related techniques and tools.