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

Lookup NU author(s): Dr Colin Gillespie, Professor Darren Wilkinson, Dr Allyson Lister, Dr Carole Proctor

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This work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0).


Abstract

© 2020 California Institute of Technology Published under the terms of the CC BY 4.0 licenseSystems 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.


Publication metadata

Author(s): Keating SM, Waltemath D, Konig M, Zhang F, Drager A, Chaouiya C, Bergmann FT, Finney A, Gillespie CS, Helikar T, Hoops S, Malik-Sheriff RS, Moodie SL, Moraru II, Myers CJ, Naldi A, Olivier BG, Sahle S, Schaff JC, Smith LP, Swat MJ, Thieffry D, Watanabe L, Wilkinson DJ, Blinov ML, Begley K, Faeder JR, Gomez HF, Hamm TM, Inagaki Y, Liebermeister W, Lister AL, Lucio D, Mjolsness E, Proctor CJ, Raman K, Rodriguez N, Shaffer CA, Shapiro BE, Stelling J, Swainston N, Tanimura N, Wagner J, Meier-Schellersheim M, Sauro HM, Palsson B, Bolouri H, Kitano H, Funahashi A, Hermjakob H, Doyle JC, Hucka M, Adams RR, Allen NA, Angermann BR, Antoniotti M, Bader GD, Cerveny J, Courtot M, Cox CD, Dalle Pezze P, Demir E, Denney WS, Dharuri H, Dorier J, Drasdo D, Ebrahim A, Eichner J, Elf J, Endler L, Evelo CT, Flamm C, Fleming RMT, Frohlich M, Glont M, Goncalves E, Golebiewski M, Grabski H, Gutteridge A, Hachmeister D, Harris LA, Heavner BD, Henkel R, Hlavacek WS, Hu B, Hyduke DR, de Jong H, Juty N, Karp PD, Karr JR, Kell DB, Keller R, Kiselev I, Klamt S, Klipp E, Knupfer C, Kolpakov F, Krause F, Kutmon M, Laibe C, Lawless C, Li L, Loew LM, Machne R, Matsuoka Y, Mendes P, Mi H, Mittag F, Monteiro PT, Natarajan KN, Nielsen PMF, Nguyen T, Palmisano A, Pettit J-B, Pfau T, Phair RD, Radivoyevitch T, Rohwer JM, Ruebenacker OA, Saez-Rodriguez J, Scharm M, Schmidt H, Schreiber F, Schubert M, Schulte R, Sealfon SC, Smallbone K, Soliman S, Stefan MI, Sullivan DP, Takahashi K, Teusink B, Tolnay D, Vazirabad I, von Kamp A, Wittig U, Wrzodek C, Wrzodek F, Xenarios I, Zhukova A, Zucker J

Publication type: Review

Publication status: Published

Journal: Molecular Systems Biology

Year: 2020

Volume: 16

Issue: 8

Print publication date: 01/08/2020

Online publication date: 26/08/2020

Acceptance date: 09/07/2020

ISSN (electronic): 1744-4292

Publisher: Blackwell Publishing Ltd

URL: https://doi.org/10.15252/msb.20199110

DOI: 10.15252/msb.20199110

PubMed id: 32845085


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