CAJ | 학술논문

当前对于疾病分子网络的治疗多采用多靶标药物治疗。多靶标药物治疗共分为两步，首先是筛选潜在的药物靶标，其次利用筛选出的药物靶标进行组合，进而得到有效的抑制方案。但现有算法耗时太多，本文使用花生四烯酸（Arachidonic acid）炎症代谢网络作为一个具体算例，使用改进并行的粒子群算法进行多靶标筛选优化，不仅能够得到药物靶标的有效组合，而且根据进程的个数可以使计算时间达到数倍的提高。
당전대우질병분자망락적치료다채용다파표약물치료。다파표약물치료공분위량보，수선시사선잠재적약물파표，기차이용사선출적약물파표진행조합，진이득도유효적억제방안。단현유산법모시태다，본문사용화생사희산（Arachidonic acid）염증대사망락작위일개구체산례，사용개진병행적입자군산법진행다파표사선우화，불부능구득도약물파표적유효조합，이차근거진정적개수가이사계산시간체도수배적제고。
The therapy of disease‐related molecular network is usually based on the multiple target drug therapy .The multiple target drug therapy can be divided into two steps .First ,filtering the potential drug targets .Second ,making use of them to compose ,in order to find the effective inhibition scheme . However ,the present algorithm takes too much time .This article used the Arachidonic acid inflammation metabolic network as a concrete example ,and also used the improved parallel particle swarm optimization to optimize the multiple targets .As a result ,it can not only compose the drug targets effectively ,but also save more time than the present algorithm according to the number of processes .