Static analysis of stochastic rule-based models of biochemical systems

Tatjana Petrov (IST Austria)

When: June 27, 2:00pm

Where: room G2.91b/G215

Abstract

Intuitively, bisimulation is a measure of behavioural similarity between two transition systems. The classical probabilistic bisimulation on transition systems running in continous-time, on discrete state space, coincides with the concept of lumpability in Markov chain theory. In the talk, I will show how such probabilistic bisimulation can be effectively constructed for models of biochemical networks written in a rule-based language, and, thus, provide a significant state space reduction. I will then discuss a work in progress, also concerned with applying formal methods to systems and synthetic biology.