Page 1 A hybrid machine model of rice blast fungus, Magnaporthe grisea. Mike Holcombe 1 , Lucy Holcombe 2 , Marian Gheorghe 1 , Nick Talbot 2 . Abstract. The fungus, Magnaporthe grisea (Rice blast fungus) is a major agricultural problem affecting rice and related food crops. The way that the fungus in- vades the host plant and propagates itself is a very important scientific prob- lem and recent advances in research into the genetic basis of these processes can be used to build a simple partial model using hybrid computational modelling techniques. The possible potential benefits of doing this include the use of computer simulation and automated analysis through techniques such as model checking to understand the complex behaviour of such sys- tems. The example is a metaphor for the process of trying to integrate and understand much of the vast amounts of genomic and other data that is being produced in current molecular biology research. Keywords: Computational model, state machine, X-machine, agent, hybrid model, fungal infection, genomics, bioinformatics. 1. INTRODUCTION Computational models have been of interest in biology for many years and have represented a particular approach to trying to understand biological processes and phenomena from a systems point of view. Much of the early work was rather abstract and high level and probably seemed to many to be of more philosophical than practical value. There have, however, been some ad- vances in the development of more realistic models and the current state of computer science research provides us with new opportunities both through the emergence of model types that can model seriously complex systems but also the support that modern software can give to the modelling process. 2. MODELLING CONTINUOUS STATE-BASED PHENOMENA Finite state machines and their generalisations, such as X-machines [2, 6, 7, 8], are examples of discrete computational models that operate in finite environments (finite input sets, finite output sets and finite memory variables). They are suitable for modelling many types of system. How- ever they can only model instantaneous processing and only finite discrete data is processed. Continuous functions and real valued data cannot be incorporated into traditional finite state machine models. Such systems are problematic when trying to deal with the complexities of some biological models and the hybrid X-machine [1], overcomes some of these problems. A hybrid machine has states and transitions as usual and responds to discrete events and per- forms discrete actions which are observable. The internal memory consists of: a set of discrete variable and a set of continuous variables. 1.Department of Computer Science, University of Sheffield, Sheffield, S1 4DP, UK 2.Department of Biological Sciences, University of Exeter, Exeter, EX4 4QJ, UK