Cited by 174Scientific Computing and Data ManagementResearch Data Management PracticesGene Regulatory Network Analysis

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

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Bergmann, Frank T, Adams, Richard, Moodie, Stuart, Cooper, Jonathan, Glont, Mihai, Golebiewski, Martin, Hucka, Michael, Laibe, Camille +10 more·2014·BMC Bioinformatics

Abstract

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.

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  • Each entity and activity in the final set has already been mentioned for provenance, modeling or documentation purposes, or experiment design of simulation studies, but they have not all been used together.

    “Each entity and activity has already been mentioned for provenance, modeling or documentation purposes, or experiment design of simulation studies [1, 3–5, 8, 20, 21, 60–63], but they have not all been used together.”

    From Relating simulation studies by provenance—Developing a family of Wnt signaling models (2021) · cites this paper as [61]

    The Background discusses documenting models, simulation procedures, results, and metadata; Implementation > Metadata also discusses logs of actions and audit trails (pages unavailable). These passages support the claim that related concepts had been discussed for modeling, documentation, and provenance. They do not establish that every entity and activity in the citing document’s final set had been mentioned previously or that the full set had never been used together. (LLM, conf=0.82)

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  • The inclusion of all necessary protocols and data needed to implement a model enables distribution of models via a single file, encouraging reuse and improving reproducibility.

    “The inclusion of all necessary protocols and data needed to implement a model enables distribution of models via a single file encouraging reuse and improving reproducibility [55].”

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Authors
Bergmann, F. T., Adams, R., Moodie, S., Cooper, J., Glont, M., Golebiewski, M., Hucka, M., Laibe, C., Miller, A. K., Nickerson, D. P., Olivier, B. G., Rodriguez, N., Sauro, H. M., Scharm, M., Soiland-Reyes, S., Waltemath, D., Yvon, F., & Le Novère, N.
Affiliations
  • Heidelberg University (DE)
  • Research Space (United Kingdom) (GB)
  • European Bioinformatics Institute (GB)
  • University of Oxford (GB)
  • Heidelberg Institute for Theoretical Studies (DE)
  • California Institute of Technology (US)
  • University of Auckland (NZ)
  • Vrije Universiteit Amsterdam (NL)
  • University of Washington (US)
  • University of Rostock (DE)
Venue
BMC Bioinformatics
Published
2014-12
Volume
15
Issue
1
Pages
369-369
ISSN
1471-2105 (ISSN-L)
OpenAlex
W2096951208
Cited by
173
References
44
Citations by year
2026: 10 · 2025: 10 · 2024: 19 · 2023: 23 · 2022: 16 · 2021: 25 · 2020: 18 · 2019: 10 · 2018: 15 · 2017: 6 · 2016: 11 · 2015: 7 · 2014: 2 · 2013: 1
FWCI
16.81
Type
journal article
Language
en
Open access
Locations
  • BMC Bioinformatics (publishedVersion, cc-by)
  • Europe PMC (PubMed Central) (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • Research Explorer (The University of Manchester) (publishedVersion, cc-by)
  • VU Research Portal (publishedVersion, other-oa)
  • arXiv (Cornell University) (submittedVersion)
  • CaltechAUTHORS (California Institute of Technology) (submittedVersion, cc-by)
  • UCL Discovery (University College London) (submittedVersion)
  • Data Archiving and Networked Services (DANS) (submittedVersion, other-oa)
  • arXiv (Cornell University)
Funders
  • Microsoft Research
  • European Commission (283359, 270192)
  • ZonMw (40-41009-98-10038)
  • Bundesministerium für Bildung und Forschung (FKZ 031, FKZ 0316194, 0316194)
  • Innovative Medicines Initiative (115156)
  • Maurice Wilkins Centre for Molecular Biodiscovery
  • National Institutes of Health (NIH P50, GM094503)
  • Engineering and Physical Sciences Research Council (EP/I017909, EP/I017909/1)
  • Biotechnology and Biological Sciences Research Council (BB/M013189/1, BBS/E/B/000C0419)
  • National Institute of General Medical Sciences (GM070923, R01GM070923, P50GM094503, R01GM081070)
  • FP7 Information and Communication Technologies
Topics
  • Social Sciences › Decision Sciences › Information Systems and Management › Scientific Computing and Data Management
  • Physical Sciences › Computer Science › Information Systems › Research Data Management Practices
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Gene Regulatory Network Analysis
Keywords
model exchange, model reproducibility, model metadata, audit trail, multiscale modeling, digital organisms
MeSH terms
Archives, Computer Simulation, Humans, Software, Information Storage and Retrieval, Computational Biology, Internet, Databases, Nucleic Acid

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