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Sylwester Kloska

dblp:290/9559 · DBLP profile ↗
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1ranked-venue papers
1as first author
1since 2021 · last 2021
0000-0002-5165-9302ORCID · reported

Domains — the database's venue-derived domains; a paper can count in several

Applied, interdisciplinary, general and emerging computing · 1 · 1 first-author · 1 since 2021

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Interdisciplinary, comprehensive, and emerging computing
1 paper
Bioinformatics and computational biology · 100%

Topics — the 3 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Bioinformatics and computational biology › systems biology
computational systems biology
0.512021
Queueing theory model of Krebs cycle · Bioinform. 2021
Bioinformatics and computational biology › systems biology › metabolic modeling
metabolic pathway modeling
0.512021
Queueing theory model of Krebs cycle · Bioinform. 2021
Bioinformatics and computational biology › systems biology › biochemical simulation
biochemical reaction simulation
0.112021
Queueing theory model of Krebs cycle · Bioinform. 2021

Methods — techniques the papers use, named apart from their topics

queueing theory · 0.5
YearPublicationVenuePosition
2021 Queueing theory model of Krebs cycle
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.
Sylwester Kloska, Krzysztof Palczynski, Tomasz Marciniak, Tomasz Talaska, Marissa Nitz, Beata J. Wysocki, Paul H. Davis, Tadeusz A. Wysocki
Bioinform.1