Award details

Agent-Based Integrative Modelling of Bacterial Populations

Reference	BB/D006619/1
Principal Investigator / Supervisor	Professor Brian Logan
Co-Investigators / Co-Supervisors	Professor John King, Mr Michael Lees
Institution	University of Nottingham
Department	School of Computer Science
Funding type	Research
Value (£)	60,625
Status	Completed
Type	Research Grant
Start date	01/12/2005
End date	28/02/2007
Duration	15 months

Abstract

The project aims to explore the feasibility of using distributed and Grid-based simulation techniques for studying complex agent-based models of cell populations. Specifically, we will: * investigate the computational efficiency of biological simulations built using IEEE 1516 (HLA) compliant simulators instantiated and linked using Grid services; * assess the suitability of the HLA framework for biological modelling, specifically via investigations of the spatio-temporal behaviour of bacterial populations. The first objective involves establishing the overhead of the HLA-Grid protocols for biological simulations, and in particular the routing space approach to data distribution management adopted by the underlying HLA infrastructure. These factors determine the computational cost of communication between the component simulations over the Grid, and hence at what point (in terms of simulation size) distribution results in a reduction in simulation time. The second is more subjective, and involves an assessment of the appropriateness for biological problems of the object/attribute/interaction modelling framework on which the HLA is based. The suitability or otherwise of this framework is key, as it determines how difficult it will be to build biological simulations using HLA, and hence whether the advantages of simulation composition and reuse are likely to be realised. The work forms a first step towards more tailored biological Grid-based simulation environments.

Summary

In recent years major advances have been made in understanding the gene and signalling networks that control the behaviour of individuals cells. The need to understand the implications of these breakthroughs for the behaviour at the population level is increasingly widely recognised, and computational simulation has a crucial role to play in providing the necessary insight. Moreover, recent technological developments, such as the Grid, make available significantly more powerful computational resources and assist with the (often international) collaborations which will be needed if full use is to be made of the available resources and data. The proposed investigations, which focus on relatively simple bacterial cells, will take advantage of each of these advances and will seek to develop robust approaches to simulating the behaviour of large groups of cells (treating each as a separate agent). The specific focus will be on studying the development of bacterial biofilms (these having many important industrial, medical and environmental implications), investigating how the interactions between individual cells can lead to the highly-complex structures seen in practice.

Committee	Closed Committee - Engineering & Biological Systems (EBS)
Research Topics	X – not assigned to a current Research Topic
Research Priority	X – Research Priority information not available
Research Initiative	EDF (e-science Development Fund) (EDF) [2003-2005]
Funding Scheme	X – not Funded via a specific Funding Scheme

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