| Autor: |
Austen Bernardi, Jessica M.J. Swanson |
| Jazyk: |
angličtina |
| Rok vydání: |
2021 |
| Předmět: |
|
| Zdroj: |
SoftwareX, Vol 14, Iss , Pp 100676- (2021) |
| Druh dokumentu: |
article |
| ISSN: |
2352-7110 |
| DOI: |
10.1016/j.softx.2021.100676 |
| Popis: |
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. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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