可编程微流控装置的流体加载优化

Satoru Maruyama, Debraj Kundu, S. Yamashita, Sudip Roy
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引用次数: 3

摘要

可编程微流控器件(Programmable Microfluidic Device, PMD)作为一种新型的微流控生物芯片,近年来受到了设计自动化界的广泛关注。对于PMD芯片的设计,重要的任务之一是在执行生物方案之前,通过创建一些流体流,将反应物流体加载到特定细胞中的流量减少到最小。尽管这个问题很重要,但几乎没有研究这个问题的工作。因此,本文对PMD芯片中的流体加载问题进行了深入的研究。首先,我们成功地将问题表述为约束满足问题(CSP),从而首次实现了问题的最优解。然后,我们还提出了一种有效的启发式方法,称为从最后确定流(DFL)方法,用于较大的问题实例。DFL基于一种新颖的想法,即与最先进的PMD (FLAP)流体加载算法(Fluid Loading Algorithm for PMD, FLAP)不同,从最后一个流中确定流量更好[Gupta等人,TODAES, 2019]。仿真结果表明,精确方法可以找到实际测试用例的最优解,而启发式方法可以找到近似最优解,优于FLAP方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Optimization of Fluid Loading on Programmable Microfluidic Devices for Bio-protocol Execution
Recently, Programmable Microfluidic Device (PMD) has got an attention of the design automation communities as a new type of microfluidic biochips. For the design of PMD chips, one of the important tasks is to minimize the number of flows for loading the reactant fluids into specific cells (by creating some flows of the fluids) before the bio-protocol is executed. Nevertheless of the importance of the problem, there has been almost no work to study this problem. Thus, in this paper, we intensively study this fluid loading problem in PMD chips. First, we successfully formulate the problem as a constraint satisfaction problem (CSP) to solve the problem optimally for the first time. Then, we also propose an efficient heuristic called Determining Flows from the Last (DFL) method for larger problem instances. DFL is based on a novel idea that it is better to determine the flows from the last flow unlike the state-of-the-art method Fluid Loading Algorithm for PMD (FLAP) [Gupta et al., TODAES, 2019]. Simulation results confirm that the exact method can find the optimal solutions for practical test cases, whereas our heuristic can find near-optimal solutions, which are better than those obtained by FLAP.
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