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Published December 14, 2014 | Supplemental Material + Published
Journal Article Open

COMBINE archive and OMEX format: one file to share all information to reproduce a modeling project


Background: With the ever increasing use of computational models in the biosciences, the need to share models and reproduce the results of published studies efficiently and easily is becoming more important. To this end, various standards have been proposed that can be used to describe models, simulations, data or other essential information in a consistent fashion. These constitute various separate components required to reproduce a given published scientific result. Results: We describe the Open Modeling EXchange format (OMEX). Together with the use of other standard formats from the Computational Modeling in Biology Network (COMBINE), OMEX is the basis of the COMBINE Archive, a single file that supports the exchange of all the information necessary for a modeling and simulation experiment in biology. An OMEX file is a ZIP container that includes a manifest file, listing the content of the archive, an optional metadata file adding information about the archive and its content, and the files describing the model. The content of a COMBINE Archive consists of files encoded in COMBINE standards whenever possible, but may include additional files defined by an Internet Media Type. Several tools that support the COMBINE Archive are available, either as independent libraries or embedded in modeling software. Conclusions: The COMBINE Archive facilitates the reproduction of modeling and simulation experiments in biology by embedding all the relevant information in one file. Having all the information stored and exchanged at once also helps in building activity logs and audit trails. We anticipate that the COMBINE Archive will become a significant help for modellers, as the domain moves to larger, more complex experiments such as multi-scale models of organs, digital organisms, and bioengineering.

Additional Information

© 2014 Bergmann et al.; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. Received: 4 July 2014 Accepted: 30 October 2014. Published online: 14 December 2014. SM, MG, CL received funding from the Innovative Medicines Initiative Joint Undertaking (grant agreement no. 115156, DDMoRe). JC was supported through the EPSRC Cross-Disciplinary Interface Programme (grant number EP/I017909/1) and Microsoft Research Ltd. MH and NR were supported by US National Institute of General Medical Sciences (GM070923). DPN is supported by The Virtual Physiological Rat Project (NIH P50-GM094503) and the Maurice Wilkins Centre for Molecular Biodiversity. BO is supported by a ZonMW Zenith grant 40-41009-98-10038. HMS was partly supported by US National Institute of General Medical Sciences (R01GM081070). MS and DW are funded by the German Federal Ministry of Education and Research (e:Bio program SEMS, FKZ 031 6194). SSR was supported by the EU (FP7 RI-283359 and FP7-ICT-2007-6 270192). NR and NLN were supported by the UK Biotechnology and Biological Science Research Council (BBS/E/B/000C0419).

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