A combinatorial approach to reconstruct Petri nets from experimental data

Abstract

For many aspects of health and disease, it is important to understand different phenomena in biology and medicine. To gain the required insight, experimental data are provided and need to be interpreted, thus the challenging task is to generate all models that explain the observed phenomena. In systems biology the framework of Petri nets is often used to describe models for the regulatory mechanisms of biological systems. The aim of this paper is to present an exact combinatorial approach for the reconstruction of such models from experimental data. © 2008 Springer Berlin Heidelberg.