From Petrinets to Partial Differential Equations - A Petrinet perspective on systems and synthetic biology
Van Leeuwenhoek Lecture on BioScience.
Drinks after the lecture
Monika Heiner is Professor for Data Structures and Software Dependability, Computer Science Deparment of the Brandenburg University of Technology Cottbus-Senftenberg. She is also visiting professor at Brunel University London, College of Engineering, Design and Physical Sciences, Computer Science and Synthetic Biology Theme.
She studied computer sciences at the University of Technology at Dresden and graduated in 1980 at the same University, where she was a scientific staff member from 1980 until 1984.
From 1984 - 1991 she was a scientific staff member at the Institute of Informatiques and Computer Technique of GMD at Berlin. (software validation using Petri nets).
From 1992-1994 she had the same function at the Institute of Computer Architecture and Software technique of GMD at Berlin. After that she went to Berkeley for a research stage (International Computer Science Institute).
In 1994 she accepted a professorship at the Brandenburg University of Technology in Cottbus.
She had several sabbatical leaves:
- 1999/2000 Boston University, Metropolitan College (course: object-oriented analysis and design, software technology)
- 2003, University of Costa Rica/San Jose (course: validation of embedded systems)
- 2007, INRIA Rocqencourt (biochemical network analysis)
- March 2010: Universidad de Zaragoza (autonomous continuous Petri nets)
- 2011: visiting professor at Brunel University, London (Petri nets for multiscale systems)
- 2013: visiting professor at Laboratoire Specification et Verification, Cachan/ Paris
- 2015: visiting professor at Brunel University, London , Centre Systems and Synthetic Biology
Monika Heiner published several books and many articles.
She was/is a member of many Programme Committees.
She is in the editorial board of Natural Computing, AIMS Bioengineering, Computational Methods in Systems Biology.
Petri nets offer a graphical & intuitive notation for biochemical networks. May be even more importantly, they are a convenient choice for an umbrella formalism combining different modelling paradigms, where each perspective contributes toa better understanding of the biochemical system under study. In this spirit of BioModel Engineering, we developed over the last two decades our unifying Petri net framework comprising the traditional time-free Petri nets (PN) as well as quantitative,i.e. time-dependent Petri nets such as stochastic Petri nets (SPN), continuous Petri nets (CPN), and hybrid Petri nets (HPN), as well as their coloured counterparts
Coloured Petri nets permit, among others, the convenient and flexible encoding of spatial attributes, and thus the modelling of processes evolving in time and space, which are usually considered as stochastic or deterministic reaction-diffusion systems by help of stochastic or deterministic partial differential equations. In our approach, the discretisation of space already happens on the modelling level, while traditionally the discretisation is left for the PDE integration methods.
Our framework is supported by a related Petri net toolkit comprising Snoopy, Charlie and Marcie. It has been applied to a couple of case studies. Those involving spatial aspects include the Brusselator model to explore Turing patterns, C. elegans vulval development, stochastic membrane systems composed of active compartments, Ca2+ channels arranged in two-dimensional space, phase variation in bacterial colony growth, and Planar Cell Polarity (PCP) signaling in Drosophila wing. Some of them will be sketched in this talk.