Kloska Sylwester, Pałczyński Krzysztof, Marciniak Tomasz, Talaśka Tomasz, Nitz Marissa, Wysocki Beata J, Davis Paul, Wysocki Tadeusz A
Faculty of Medicine, Nicolaus Copernicus University Ludwik Rydygier Collegium Medicum, 85-067 Bydgoszcz, Poland.
Faculty of Telecommunications, Computer Science and Electrical Engineering, UTP University of Science and Technology, 85-796 Bydgoszcz, Poland.
Bioinformatics. 2021 Sep 29;37(18):2912-2919. doi: 10.1093/bioinformatics/btab177.
Queueing theory can be effective in simulating biochemical reactions taking place in living cells, and the article paves a step toward development of a comprehensive model of cell metabolism. Such a model could help to accelerate and reduce costs for developing and testing investigational drugs reducing number of laboratory animals needed to evaluate drugs.
The article presents a Krebs cycle model based on queueing theory. The model allows for tracking of metabolites concentration changes in real time. To validate the model, a drug-induced inhibition affecting activity of enzymes involved in Krebs cycle was simulated and compared with available experimental data.
The source code is freely available for download at https://github.com/UTP-WTIiE/KrebsCycleUsingQueueingTheory, implemented in C# supported in Linux or MS Windows.
Supplementary data are available at Bioinformatics online.
排队论可有效地模拟活细胞中发生的生化反应，本文为细胞代谢综合模型的开发迈出了一步。这样的模型有助于加快研发和测试研究性药物的速度并降低成本，减少评估药物所需的实验动物数量。
本文提出了一个基于排队论的 Krebs 循环模型。该模型能够实时追踪代谢物浓度变化。为验证该模型，模拟了药物诱导的对 Krebs 循环中相关酶活性的抑制作用，并与现有实验数据进行了比较。
源代码可在 https://github.com/UTP-WTIiE/KrebsCycleUsingQueueingTheory 上免费下载，用 C# 实现，支持 Linux 或 MS Windows 系统。
补充数据可在《生物信息学》在线获取。
