Abstract
A glut of Systems Biology tools and their lack of accessibility has significantly delayed bioscience advances that depend on the analysis of large scale systems with big datasets and High Performance Computing (HPC) resources. This work presents SBMLDock, the first Systems Biology Docker image that aims to advance scalability, usability and reproducibility in Systems Biology by making tools much more immediately available to the biological domain scientist, student, and educator, without requiring special training for use, and without losing the reproducibility aspect of their research. SBMLDock consists of one Docker image containing basic tools developed for Systems Biology Model manipulation (parallel model similarity analyzer, model checker, model splitter, model annotation, model extractor). The user can then pull up the Docker image, customize it and/or run each tool as service. Stored on the Docker hub, the image version is managed to assure research reproducibility. SBMLDock is available as a Docker file under CC licence at github https://github.com/USDBioinformatics/SBMLDock and the Docker image can be found in Docker hub at https://registry.hub.docker.com/u/usdbioinformatics/sbmldock/ with supplementary documents.
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Acknowledgement
This work has been partially supported by the National Science Foundation/EPSCoR Award No. IIA-1355423 and by the state of South Dakota, through BioSNTR.
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Gnimpieba, E.Z., Thavappiragasam, M., Chango, A., Conn, B., Lushbough, C.M. (2015). SBMLDock: Docker Driven Systems Biology Tool Development and Usage. In: Roux, O., Bourdon, J. (eds) Computational Methods in Systems Biology. CMSB 2015. Lecture Notes in Computer Science(), vol 9308. Springer, Cham. https://doi.org/10.1007/978-3-319-23401-4_24
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DOI: https://doi.org/10.1007/978-3-319-23401-4_24
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