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Data model for biopart datasheets
File(s)
Author(s)
Sainz de Murieta, Inaki
Bultelle, Matthieu
Kitney, Richard
Type
Journal Article
Abstract
This study introduces a new data model, based on the DICOM-SB (see glossary of terms for definition of acronyms) standard for synthetic biology, that is capable of describing/incorporating the data, metadata and ancillary information from detailed characterisation experiments - to present DNA components (bioparts) in datasheets. The data model offers a standardised mechanism to associate bioparts with data and information about component performance - in a particular biological context (or a range of contexts, e.g. chassis). The data model includes the raw, experimental data for each characterisation run, and the protocol details needed to reliably reproduce the experiment. In addition, it provides metrics (e.g. relative promoter units, synthesis/growth rates etc.) that constitute the main content of a biopart datasheet. The data model has been developed to directly link to DICOM-SB, but also to be compatible with existing data standards, e.g. SBOL and SBML. It has been implemented within the latest version of the API that enables access to the SynBIS information system. The work should contribute significantly to the current standardisation effort in synthetic biology. The standard data model for datasheets is seen as a necessary step towards effective interoperability between part repositories, and between repositories and BioCAD applications.
Date Issued
2018-03-01
Date Acceptance
2017-12-07
Citation
Engineering Biology, 2018, 2 (1), pp.7-18
URI
URL
DOI
ISSN
2398-6182
Publisher
Institution of Engineering and Technology (IET)
Start Page
7
End Page
18
Journal / Book Title
Engineering Biology
Volume
2
Issue
1
Copyright Statement
© 2018 The Author(s). This is an open access article published by the IET under the Creative Commons
Attribution License (http://creativecommons.org/licenses/by/3.0/
Sponsor
Engineering & Physical Science Research Council (E
Engineering & Physical Science Research Council (EPSRC)
Identifier
https://ietresearch.onlinelibrary.wiley.com/doi/10.1049/enb.2017.0020
Grant Number
EP/J02175X/1
EP/L011573/1
Publication Status
Published
Date Publish Online
2018-02-28