Wu Jingli, Wang Jianxin, Chen Jian'er
School of Information Science and Engineering, Central South University, Changsha 410083, China.
Int J Bioinform Res Appl. 2009;5(1):38-49. doi: 10.1504/IJBRA.2009.022462.
Selecting the minimum primer set with multiple constraints is an effective method for a successful and economical Multiplex Polymerase Chain Reaction (MP-PCR) experiment. However, there is no suitable algorithm for solving the problem. In this paper, a mathematical model is presented for the minimum primer set selection problem with multiple constraints. By introducing a novel genetic operator, we developed a parthenogenetic algorithm MG-PGA to solve the model. Experimental results show that MG-PGA can not only find a small primer set, but can also satisfy multiple biological constraints. Therefore, MG-PGA is a practical solution for MP-PCR primer design.
选择具有多种约束条件的最小引物集是成功且经济的多重聚合酶链反应（MP-PCR）实验的有效方法。然而，没有合适的算法来解决该问题。本文针对具有多种约束条件的最小引物集选择问题提出了一个数学模型。通过引入一种新颖的遗传算子，我们开发了孤雌生殖算法MG-PGA来求解该模型。实验结果表明，MG-PGA不仅可以找到一个较小的引物集，还能满足多种生物学约束。因此，MG-PGA是MP-PCR引物设计的一种实用解决方案。
