Modularization of biochemical networks based on classification of Petri net t-invariants

Background: Structural analysis of biochemical networks is a growing field in bioinformatics and systems biology. The availability of an increasing amount of biological data from molecular biological networks promises a deeper understanding but confronts researchers with the problem of combinatorial explosion. The amount of qualitative network data is growing much faster than the amount of quantitative data, such as enzyme kinetics. In many cases it is even impossible to measure quantitative data because of limitations of experimental methods, or for ethical reasons. Thus, a huge amount of qualitative data, such as interaction data, is available, but it was not sufficiently used for modeling purposes, until now. New approaches have been developed, but the complexity of data often limits the application of many of the methods. Biochemical Petri nets make it possible to explore static and dynamic qualitative system properties. One Petri net approach is model validation based on the comp...

• Type: Journal
• Year: 2008
• Where: BMCBI
• Authors: Eva Grafahrend-Belau, Falk Schreiber, Monika Heiner, Andrea Sackmann, Björn H. Junker, Stefanie Grunwald, Astrid Speer, Katja Winder, Ina Koch
• Keywords: Biochemical Petri, BMCBI 2008, Petri Nets, Quantitative Data