Invitation to lecture on Biochemical Switching Algorithms
14 June 2012
Dr Luca Cardelli, Assistant Director at Microsoft Research in Cambridge, will deliver the Newton Institute Lecture on Biochemical Switching Algorithms.
Dr Cardelli is well-known for his research in type theory and operational semantics. Among other contributions, he helped design Modula-3, implemented the first compiler for the (non-pure) functional programming language ML, and defined the concept of typeful programming. Recently, he helped develop the Polyphonic C# experimental programming language.
The Lecture will take place as follows:
Date: Monday 16 July 2012
Venue: Liverpool John Moores University, Egerton Court, 2 Rodney Street, Liverpool L1 2UA
Pre-lecture refreshments will be provided from 5.30pm
All staff and students are invited to attend the Lecture. The event is free, but spaces are limited.
To register your attendance visit: http://buyonline.ljmu.ac.uk/browse/extra_info.asp?compid=1&modid=2&prodid=96&deptid=61&catid=9
Biological systems have been traditionally, and quite successfully, studied as 'dynamical systems', that is, as continuous systems defined by differential equation and investigated by sophisticated analysis of their continuous state space. More recently, in order to cope with the combinatorial complexity of some of these systems, they have been modelled as 'reactive systems', that is, as discrete systems defined by their patterns of interactions and investigated by techniques that come from software and hardware analysis.
There are growing formal connections being developed between those approaches, and tools and techniques that span both. Beyond those, the two approaches can be usefully combined to bring new insights to specific examples. In one direction we can ask 'what algorithm does a dynamical system implement' and in the opposite direction we can ask 'what is the dynamics of a reactive system as a whole'. Answers to these questions can establish links between the structure of a system, which is dictated by the algorithm it implements, and the function of the system, which is represented by its dynamic behaviour. Since there is depth on both sides, in the intricacies of the algorithms, and in the complexity of the dynamics, a better understanding can emerge of whole systems.
I will focus in particular on a connection between a clever and well-studied distributed computing algorithm, and a simple chemical system (4 reactions). That leads to a connection between that algorithm and a well-known biological switch that is universally found as part of cell cycle oscillators. I will also discuss a general network structure for oscillators, based on the above switches, and how they are implemented 'in practice' in natural systems. These connections are examples of 'network transformations' that preserve some desirable functionality while relaxing constraints (e.g. chemical constraints) on the system.