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QSSPN specifications

Information


Unique identifier OMICS_16917
Name QSSPN
Alternative name quasi-steady state Petri nets
Software type Package/Module
Interface Command line interface
Restrictions to use None
Input data The model input files can be created in general Petri Net editor Snoopy or directly written as text files.
Input format TXT
Operating system Unix/Linux, Mac OS, Windows
License GNU General Public License version 3.0
Computer skills Advanced
Stability Stable
Maintained Yes

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Maintainer


  • person_outline Andrzej Kierzek <>

Publication for quasi-steady state Petri nets

QSSPN in publications

 (3)
PMCID: 5732473
PMID: 29246152
DOI: 10.1186/s12918-017-0520-3

[…] was constructed in mufins [], in which ode-based networks are represented in petri net (pn) formalism and linked to the gsmn through special directed arcs using our quasi steady-state petri net (qsspn) approach []. this allows connection of metabolite (fluxes) between the pn and gsmn parts of the model, as well as the setting of flux bounds within the gsmn by the pn part of the model., […]

PMCID: 5702902
PMID: 28782239
DOI: 10.1002/psp4.12230

[…] perturbations, such as exposure to chronic stress and patient‐specific liver metabolism (figure ). the multiscale model used in our example was built using mufins software and simulated using the qsspn simulator (available as part of the mufins package). the model and software required for its execution are available in the supplementary material., we have used the human pbpk model […]

PMCID: 4653486
PMID: 26635852
DOI: 10.3389/fpls.2015.01029

[…] were detected in 13 chromosomal regions using a recombinant inbreb line (ril) population derived from the cross nanda 2419 × wangshuibai and an immortalized f2(if2) population (ma et al., ). qtls qsspn.nau-4a and qsspn.nau-5a were detected in both populations. one qtl for floret infertility was detected in the interval xwmc112-xbarc168 in chromosome 2d using a xiaoyan 54 × jing 411 ril […]


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QSSPN institution(s)
Faculty of Health and Medical Sciences, School of Biosciences and Medicine, University of Surrey, Guildford, Surrey, UK
QSSPN funding source(s)
This work was supported by Biotechnology and Biological Sciences Research Council grant BB/I008195/1 and Era SysBioPlus TB-HOST-NET grant (BB/I00453X/1).

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