Ion Channel Modeling and Simulation Using Hybrid Functional Petri Net
Neural system and ion channels remain one of the most intractable issues in biology over years because of its complexity. A representation that takes in both the intuition of biologists and the computational ability of the ion channel system is of great importance. In this paper, we exploit Hybrid Functional Petri net (HFPN) for representing ion channel dynamics. As an extension of Petri net, HFPN allows both discrete and continuous factors and realizes ordinary differential equations (ODE) which make it easy to handle biological factors in the ion channel system such as the open(close) state of ion channels and the influx (efflux) of various ions. We prove that neural elements can be naturally translated into HFPN. Simulation results of the action potential show our model very effective. Our work explores a novel approach for neuroscience research and a new application for Petri-net based method.
Hybrid Functional Petri net Dynamic model Intuitive Ion channel Action potential
Yin Tang Fei Wang
Shanghai Key Lab of Intelligent Information Processing, Fudan University, Shanghai, China
国际会议
无锡
英文
404-412
2010-09-17（万方平台首次上网日期，不代表论文的发表时间）