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dc.contributor.author
Keating, Sarah M.
dc.contributor.author
Gómez, Harold F.
dc.contributor.author
Stelling, Jörg
dc.contributor.author
et al.
dc.contributor.author
SBML Level 3 Community members
dc.date.accessioned
2020-09-29T12:32:42Z
dc.date.available
2020-09-29T12:32:42Z
dc.date.issued
2020-08-01
dc.identifier.issn
1744-4292
dc.identifier.other
10.15252/msb.20199110
en_US
dc.identifier.uri
http://hdl.handle.net/20.500.11850/443486
dc.identifier.doi
10.3929/ethz-b-000438614
dc.description.abstract
Systems biology has experienced dramatic growth in the number, size, and complexity of computational models. To reproduce simulation results and reuse models, researchers must exchange unambiguous model descriptions. We review the latest edition of the Systems Biology Markup Language (SBML), a format designed for this purpose. A community of modelers and software authors developed SBML Level 3 over the past decade. Its modular form consists of a core suited to representing reaction‐based models and packages that extend the core with features suited to other model types including constraint‐based models, reaction‐diffusion models, logical network models, and rule‐based models. The format leverages two decades of SBML and a rich software ecosystem that transformed how systems biologists build and interact with models. More recently, the rise of multiscale models of whole cells and organs, and new data sources such as single‐cell measurements and live imaging, has precipitated new ways of integrating data with models. We provide our perspectives on the challenges presented by these developments and how SBML Level 3 provides the foundation needed to support this evolution.
en_US
dc.format
application/pdf
en_US
dc.language.iso
en
en_US
dc.publisher
EMBO Press
en_US
dc.rights.uri
http://creativecommons.org/licenses/by/4.0/
dc.subject
Computational modeling
en_US
dc.subject
File format
en_US
dc.subject
Reproducibility
en_US
dc.subject
Systems biology
en_US
dc.title
SBML Level 3: an extensible format for the exchange and reuse of biological models
en_US
dc.type
Review Article
dc.rights.license
Creative Commons Attribution 4.0 International
dc.date.published
2020-08-26
ethz.journal.title
Molecular Systems Biology
ethz.journal.volume
16
en_US
ethz.journal.issue
8
en_US
ethz.journal.abbreviated
Mol Syst Biol
ethz.pages.start
e9110
en_US
ethz.size
21 p.
en_US
ethz.version.deposit
publishedVersion
en_US
ethz.identifier.wos
ethz.identifier.scopus
ethz.publication.place
Heidelberg
en_US
ethz.publication.status
published
en_US
ethz.leitzahl
ETH Zürich::00002 - ETH Zürich::00012 - Lehre und Forschung::00007 - Departemente::02060 - Dep. Biosysteme / Dep. of Biosystems Science and Eng.::03699 - Stelling, Jörg / Stelling, Jörg
ethz.leitzahl.certified
ETH Zürich::00002 - ETH Zürich::00012 - Lehre und Forschung::00007 - Departemente::02060 - Dep. Biosysteme / Dep. of Biosystems Science and Eng.::03699 - Stelling, Jörg / Stelling, Jörg
ethz.date.deposited
2020-09-04T20:16:02Z
ethz.source
SCOPUS
ethz.source
WOS
ethz.eth
yes
en_US
ethz.availability
Open access
en_US
ethz.rosetta.installDate
2020-09-29T12:32:54Z
ethz.rosetta.lastUpdated
2022-03-29T03:14:34Z
ethz.rosetta.versionExported
true
dc.identifier.olduri
http://hdl.handle.net/20.500.11850/438614
dc.identifier.olduri
http://hdl.handle.net/20.500.11850/442182
ethz.COinS
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