摘要
为获取从任意起始代谢物到目标代谢物的生化相关性较好的代谢路径,提出一种融合原子交换特征信息的基于约束的代谢路径预测算法PVA。结合代谢网络中具有的原子交换特征信息,建立一种基于约束的混合整数线性规划(MILP)代谢路径预测模型,以搜索从任意起始代谢物到目标代谢物并包含特定原子交换信息的代谢路径。实验结果表明,与同类方法相比,PVA能够有效地发现生化相关性更好的代谢路径。
To search the metabolic pathways with better biochemical correlation from an arbitrary starting metabolite to the given target metabolite,the constraint-based method called PVA was proposed to predict metabolic pathways by fusing atom exchange feature information.The atom exchange feature information in the metabolic network was combined to construct a constraint-based mixed integer linear program(MILP)model for searching the metabolic pathways containing specific atom exchange from an arbitrary starting metabolite to the given target metabolite.Experimental results demonstrate that compared with existing methods,the proposed method PVA can effectively find better biochemically feasible metabolic pathways.
作者
黄毅然
万志远
钟诚
HUANG Yi-ran;WAN Zhi-yuan;ZHONG Cheng(School of Computer and Electronics and Information,Guangxi University,Nanning 530004,China;Key Laboratory of Parallel and Distributed Computing Technology in Guangxi Universities,Guangxi University,Nanning 530004,China;Guangxi Key Laboratory of Multimedia Communications and Network Technology,Guangxi University,Nanning 530004,China)
出处
《计算机工程与设计》
北大核心
2024年第4期1087-1092,共6页
Computer Engineering and Design
基金
国家自然科学基金项目(61862006、61861004)
广西自然科学基金项目(2020GXNSFAA159074)。
关键词
代谢网络
代谢路径预测
原子交换
混合整数线性规划
化学计量
路径优化
代谢工程
metabolic network
metabolic pathway prediction
atom exchange
mixed integer linear program
stoichiometry
pathway optimization
metabolic engineering
