In this section

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:2016:10.1021/acssynbio.5b00222,
author = {Sainz, de Murieta I and Bultelle, M and Kitney, RI},
doi = {10.1021/acssynbio.5b00222},
journal = {ACS Synthetic Biology},
pages = {817--826},
title = {Toward the first data acquisition standard in synthetic biology},
url = {http://dx.doi.org/10.1021/acssynbio.5b00222},
volume = {5},
year = {2016}
}

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RIS format (EndNote, RefMan)

TY - JOUR
AB - This paper describes the development of a new data acquisition standard for synthetic biology. This comprises the creation of a methodology that is designed to capture all the data, metadata, and protocol information associated with biopart characterization experiments. The new standard, called DICOM-SB, is based on the highly successful Digital Imaging and Communications in Medicine (DICOM) standard in medicine. A data model is described which has been specifically developed for synthetic biology. The model is a modular, extensible data model for the experimental process, which can optimize data storage for large amounts of data. DICOM-SB also includes services orientated toward the automatic exchange of data and information between modalities and repositories. DICOM-SB has been developed in the context of systematic design in synthetic biology, which is based on the engineering principles of modularity, standardization, and characterization. The systematic design approach utilizes the design, build, test, and learn design cycle paradigm. DICOM-SB has been designed to be compatible with and complementary to other standards in synthetic biology, including SBOL. In this regard, the software provides effective interoperability. The new standard has been tested by experiments and data exchange between Nanyang Technological University in Singapore and Imperial College London.
AU - Sainz,de Murieta I
AU - Bultelle,M
AU - Kitney,RI
DO - 10.1021/acssynbio.5b00222
EP - 826
PY - 2016///
SN - 2161-5063
SP - 817
TI - Toward the first data acquisition standard in synthetic biology
T2 - ACS Synthetic Biology
UR - http://dx.doi.org/10.1021/acssynbio.5b00222
UR - https://pubs.acs.org/doi/10.1021/acssynbio.5b00222
UR - http://hdl.handle.net/10044/1/33576
VL - 5
ER -