Department of Mathematics, Shanghai University, Shanghai 200444, People's Republic of China.
J Chem Phys. 2012 Apr 14;136(14):144108. doi: 10.1063/1.3702433.
In biochemical reaction systems dominated by delays, the simulation speed of the stochastic simulation algorithm depends on the size of the wait queue. As a result, it is important to control the size of the wait queue to improve the efficiency of the simulation. An improved accelerated delay stochastic simulation algorithm for biochemical reaction systems with delays, termed the improved delay-leaping algorithm, is proposed in this paper. The update method for the wait queue is effective in reducing the size of the queue as well as shortening the storage and access time, thereby accelerating the simulation speed. Numerical simulation on two examples indicates that this method not only obtains a more significant efficiency compared with the existing methods, but also can be widely applied in biochemical reaction systems with delays.
在以延迟为主导的生化反应系统中,随机模拟算法的模拟速度取决于等待队列的大小。因此,控制等待队列的大小对于提高模拟效率非常重要。本文提出了一种改进的带延迟的生化反应系统加速延迟随机模拟算法,称为改进的延迟跳跃算法。该算法的等待队列更新方法能够有效减小队列的大小,缩短存储和访问时间,从而加速模拟速度。通过对两个例子的数值模拟表明,该方法不仅比现有方法具有更高的效率,而且可以广泛应用于带延迟的生化反应系统。