## Wednesday, 28 October 2009

### Venue: Microsoft Research Cambridge, Small Lecture Theatre

### Chair: Sean Sedwards

14:00 | Colonies of Synchronizing Agents |

Radu Mardare (CoSBi) | |

14:30 | Taming the Complexity of Biological Pathways through Parallel Computing |

Davide Prandi (CoSBi) | |

15:00 | Dynamic Spatial Games and Developmental Biology |

Sean Sedwards (CoSBi) |

## Colonies of Synchronizing Agents

We introduce a modelling framework and computational paradigm called Colonies of Synchronizing Agents (CSAs) inspired by the intracellular and intercellular mechanisms in biological tissues. The model is based on a multiset of agents in a common environment. Each agent has a local state stored in the form of a multiset of atomic objects, which is updated by global multiset rewriting rules either independently or synchronously with another agent. We first define the model then study its computational power, considering tradeoffs between internal rewriting (intracellular mechanisms) and synchronization between agents (intercellular mechanisms). We also investigate dynamic properties of CSAs, including behavioural robustness (ability to generate a core behaviour despite agent loss or rule failure) and safety of synchronization (ability of an agent to synchronize with some other agent whenever needed).

## Taming the Complexity of Biological Pathways through Parallel Computing

Biological systems are characterised by a large number of interacting entities, molecules of different species whose dynamics is described by a number of reaction equations. Mathematical methods for modelling of biological systems are mostly based on a centralised solution approach: the modelled system is described as a whole and the solution technique, being it obtained through integration of a system of ODEs or by simulation of a stochastic model, is commonly calculated in a centralised fashion. In recent times research efforts moved towards the definition of parallel/distributed algorithms as a means to tackle the complexity of biological models analysis. In this talk we present a survey on the progress of such parallelization efforts describing the most promising results so far obtained.

## Dynamic Spatial Games and Developmental Biology

Dynamic Spatial Games is a generative model based on graph grammars and game theory. The idea of the model is to generate complex networks by iterative node-based transformations determined by local interactions. The node-based transformations are controlled by graph grammars, while the interactions between the nodes are represented by a game theoretical model. In the presented application, two-dimensional cellular tissues are modelled by triangulated graphs and cell division and death are represented by graph-grammar productions. Dynamic Spatial Games thus facilitates the investigation of intercellular interactions in developmental biology as cooperation and competition. In this way, for example, it is possible to define and quantify cooperation and competition between normal cells, partially mutated cells and tumour cells in tumourgenesis.