Asynchronous adaptive time step in quantitative cellular automata modeling

Background: The behaviors of cells in metazoans are context dependent, thus large-scale multicellular modeling is often necessary, for which cellular automata are natural candidates. Two related issues are involved in cellular automata based multi-cellular modeling: how to introduce differential equation based quantitative computing to precisely describe cellular activity, and upon it, how to solve the heavy time consumption issue in simulation. Results: Based on a modified, language based cellular automata system we extended that allows ordinary differential equations in models, we introduce a method implementing asynchronous adaptive time step in simulation that can considerably improve efficiency yet without a significant sacrifice of accuracy. An average speedup rate of 4

• Type: Journal
• Year: 2004
• Where: BMCBI
• Authors: Hao Zhu, Peter Y. H. Pang, Yan Sun, Pawan Dhar
• Keywords: BMCBI 2004, Cellular Automata, Large-scale Multicellular Modeling, Multi-cellular Modeling