CycFlowDec: A Python module for decomposing flow networks using simple cycles

New algorithms for determining the expected flow through simple cycles in a closed network are presented. Current network analysis software do not implement algorithms for expected cyclic flow decomposition, despite its potential value. Decomposing networks into expected cycle flows provides a quant...

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Published inSoftwareX Vol. 14; p. 100676
Main Authors Bernardi, Austen, Swanson, Jessica M.J.
Format Journal Article
LanguageEnglish
Published Elsevier B.V 01.06.2021
Elsevier
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ISSN2352-7110
2352-7110
DOI10.1016/j.softx.2021.100676

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Abstract New algorithms for determining the expected flow through simple cycles in a closed network are presented. Current network analysis software do not implement algorithms for expected cyclic flow decomposition, despite its potential value. Decomposing networks into expected cycle flows provides a quantitative characterization of network cycles that can be further analyzed for sensitivity and correlative behavior. An efficient, general algorithm has been coded into CycFlowDec, an open source Python module available at https://github.com/austenb28/CycFlowDec.
AbstractList New algorithms for determining the expected flow through simple cycles in a closed network are presented. Current network analysis software do not implement algorithms for expected cyclic flow decomposition, despite its potential value. Decomposing networks into expected cycle flows provides a quantitative characterization of network cycles that can be further analyzed for sensitivity and correlative behavior. An efficient, general algorithm has been coded into CycFlowDec, an open source Python module available at https://github.com/austenb28/CycFlowDec.
New algorithms for determining the expected flow through simple cycles in a closed network are presented. Current network analysis software do not implement algorithms for expected cyclic flow decomposition, despite its potential value. Decomposing networks into expected cycle flows provides a quantitative characterization of network cycles that can be further analyzed for sensitivity and correlative behavior. An efficient, general algorithm has been coded into CycFlowDec, an open source Python module available at https://github.com/austenb28/CycFlowDec.New algorithms for determining the expected flow through simple cycles in a closed network are presented. Current network analysis software do not implement algorithms for expected cyclic flow decomposition, despite its potential value. Decomposing networks into expected cycle flows provides a quantitative characterization of network cycles that can be further analyzed for sensitivity and correlative behavior. An efficient, general algorithm has been coded into CycFlowDec, an open source Python module available at https://github.com/austenb28/CycFlowDec.
ArticleNumber 100676
Author Swanson, Jessica M.J.
Bernardi, Austen
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Keywords Cyclic flow decomposition
Kinetic modeling
Network analysis
CycFlowDec
Kinetic networks
Language English
License This is an open access article under the CC BY-NC-ND license.
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Snippet New algorithms for determining the expected flow through simple cycles in a closed network are presented. Current network analysis software do not implement...
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SubjectTerms CycFlowDec
Cyclic flow decomposition
Kinetic modeling
Kinetic networks
Network analysis
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Title CycFlowDec: A Python module for decomposing flow networks using simple cycles
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