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Research

Biological systems - including the simplest cells - exhibit a broad range of functions to thrive in their environment. Research in the Imperial College Centre for Synthetic Biology is focused on the possibility of engineering the underlying biochemical processes to solve many of the challenges facing society, from healthcare to sustainable energy. In particular, we model, analyse, design and build biological and biochemical systems in living cells and/or in cell extracts, both exploring and enhancing the engineering potential of biology.

As part of our research we develop novel methods to accelerate the celebrated Design-Build-Test-Learn synthetic biology cycle. As such research in the Centre for Synthetic Biology highly multi- and interdisciplinary covering computational modelling and machine learning approaches; automated platform development and genetic circuit engineering ; multi-cellular and multi-organismal interactions, including gene drive and genome engineering; metabolic engineering; in vitro/cell-free synthetic biology; engineered phages and directed evolution; and biomimetics, biomaterials and biological engineering.

Publications

Citation

BibTex format

@article{Sainz:2018:10.1049/enb.2017.0020,
author = {Sainz, de Murieta I and Bultelle, M and Kitney, R},
doi = {10.1049/enb.2017.0020},
journal = {Engineering Biology},
pages = {7--18},
title = {Data model for biopart datasheets},
url = {http://dx.doi.org/10.1049/enb.2017.0020},
volume = {2},
year = {2018}
}

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RIS format (EndNote, RefMan)

TY - JOUR
AB - 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.
AU - Sainz,de Murieta I
AU - Bultelle,M
AU - Kitney,R
DO - 10.1049/enb.2017.0020
EP - 18
PY - 2018///
SN - 2398-6182
SP - 7
TI - Data model for biopart datasheets
T2 - Engineering Biology
UR - http://dx.doi.org/10.1049/enb.2017.0020
UR - https://ietresearch.onlinelibrary.wiley.com/doi/10.1049/enb.2017.0020
UR - http://hdl.handle.net/10044/1/59357
VL - 2
ER -