Queueing theory model of Krebs cycle-Reference-Cited by-同舟云学术

Queueing theory model of Krebs cycle

Published:2021-03-16 Issue:18 Volume:37 Page:2912-2919
ISSN:1367-4803
Container-title:Bioinformatics
language:en
Short-container-title:

Author:

Kloska Sylwester¹^ORCID,Pałczyński Krzysztof²,Marciniak Tomasz²,Talaśka Tomasz²,Nitz Marissa³,Wysocki Beata J⁴,Davis Paul⁴,Wysocki Tadeusz A²³

Affiliation:

1. Faculty of Medicine, Nicolaus Copernicus University Ludwik Rydygier Collegium Medicum, 85-067 Bydgoszcz, Poland

2. Faculty of Telecommunications, Computer Science and Electrical Engineering, UTP University of Science and Technology, 85-796 Bydgoszcz, Poland

3. Department of Electrical and Computer Engineering, University of Nebraska-Lincoln, Omaha, NE 68182, USA

4. Department of Biology, University of Nebraska at Omaha, Omaha, NE 68182, USA

Abstract

Abstract Motivation 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. Results 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. Availabilityand implementation 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 information Supplementary data are available at Bioinformatics online.

Funder

National Science Center

Publisher

Oxford University Press (OUP)

Subject

Computational Mathematics,Computational Theory and Mathematics,Computer Science Applications,Molecular Biology,Biochemistry,Statistics and Probability

Link

http://academic.oup.com/bioinformatics/advance-article-pdf/doi/10.1093/bioinformatics/btab177/38619622/btab177.pdf

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