A versatile petri net based architecture for modeling and simulation of complex biological processes.
The research on modeling and simulation of complex biological systems is getting more important in Systems Biology. In this respect, we have developed Hybrid Function Petri net (HFPN) that was newly developed from existing Petri net because of their intuitive graphical representation and their capabilities for mathematical analyses. However, in the process of modeling metabolic, gene regulatory or signal transduction pathways with the architecture, we have realized three extensions of HFPN, (i) an entity should be extended to contain more than one value, (ii) an entity should be extended to handle other primitive types, e.g. boolean, string, (iii) an entity should be extended to handle more advanced type called object that consists of variables and methods, are necessary for modeling biological systems with Petri net based architecture. To deal with it, we define a new enhanced Petri net called hybrid functional Petri net with extension (HFPNe). To demonstrate the effectiveness of the enhancements, we model and simulate with HFPNe four biological processes that are diffcult to represent with the previous architecture HFPN.
Nagasaki
Masao
M
Human Genome Center, Institute of Medical Science, University of Tokyo, 4-6-1 Shirokane-dai, Minato-ku, Tokyo 108-8639, Japan. masao@ims.u-tokyo.ac.jp
Doi
Atsushi
A
Matsuno
Hiroshi
H
Miyano
Satoru
S
D000465:Algorithms; D001695:Biology / Q000379:methods*; D003198:Computer Simulation; D016368:Frameshift Mutation; D006801:Humans; D006816:Huntington Disease / Q000235:genetics; D008660:Metabolism; D008954:Models, Biological; D008957:Models, Genetic; D014176:Protein Biosynthesis; D012333:RNA, Messenger / Q000235:genetics; D013269:Stochastic Processes; D016159:Tumor Suppressor Protein p53 / Q000235:genetics
D012333:RNA, Messenger; D016159:Tumor Suppressor Protein p53