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Original article | published - EPub | peer reviewed

SBML Level 3: an extensible format for the exchange and reuse of biological models


Molecular Systems Biology 2020 ; 16(8): e9110 -






Bibliometric indicators



Impact Factor = 11.429

Citations (WOS) = 0

DOI = 10.15252/msb.20199110


Authors

Keating S*, Waltemath D*1, König M, Zhang F, Dräger A, Chaouiya C, Bergmann F, Finney A, Gillespie C, Helikar T, Hoops S, Malik-Sheriff R, Moodie S, Moraru I, Myers C, Naldi A, Olivier B, Sahle S, Schaff J, Smith L, Swat M, Thieffry D, Watanabe L, Wilkinson D, Blinov M, Begley K, Faeder J


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.

Published in

Molecular Systems Biology


Year 2020
Impact Factor (2020) 11.429
Volume 16
Issue 8
Pages e9110 -
Open Access nein
Peer reviewed ja
Article type Original article
Article state published - EPub
DOI 10.15252/msb.20199110

Common journal data

Short name: MOL SYST BIOL
ISSN: 1744-4292
eISSN: 1744-4292
Country: USA
Language: English
Categories:
  • BIOCHEMISTRY & MOLECULAR BIOLOGY


Impact factor trend

Year Impact Factor
2008 12.243
2009 12.125
2010 9.667
2011 8.626
2012 11.34
2013 14.099
2014 10.872
2015 10.581
2016 9.75
2017 8.5
2018 9.8
2019 8.991
2020 11.429
2021 13.068
2022 9.9
2023 8.5
2024 7.7

Key field of research at the University



Departments

Community Medicine

Projects

Standards for in silico models for personalised medicine
Providing reproducible simulation studies targeting COVID-19 through BioModels and B2SHARE

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