Originalartikel | erschienen - EPub | peer reviewed
SBML Level 3: an extensible format for the exchange and reuse of biological models
Molecular Systems Biology
2020 ;
16(8):
e9110 -
Autoren
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
Beteiligte Einrichtungen
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.
Veröffentlicht in
Molecular Systems Biology
| Jahr | 2020 |
| Impact Factor (2020) | 11,429 |
| Volume | 16 |
| Issue | 8 |
| Seiten | e9110 - |
| Open Access | nein |
| Peer reviewed | ja |
| Artikelart | Originalartikel |
| Artikelstatus | erschienen - EPub |
| DOI | 10.15252/msb.20199110 |
Allgemeine Daten zur Fachzeitschrift
Kurzbezeichnung: MOL SYST BIOL
ISSN: 1744-4292
eISSN: 1744-4292
Land: USA
Sprache: English
Kategorie(n):
Impact Factor Entwicklung
ISSN: 1744-4292
eISSN: 1744-4292
Land: USA
Sprache: English
Kategorie(n):
- BIOCHEMISTRY & MOLECULAR BIOLOGY
Impact Factor Entwicklung
| Jahr | 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 |
Forschungsschwerpunkt der Universität
Themenschwerpunkte
Beteiligte Departments
Community Medicine
Projekte
Standards for in silico models for personalised medicine
Providing reproducible simulation studies targeting COVID-19 through BioModels and B2SHARE
Providing reproducible simulation studies targeting COVID-19 through BioModels and B2SHARE
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