Research

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Synthetic Biology underpins advances in the bioeconomy

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{Cox:2018:10.1515/jib-2017-0074,
author = {Cox, R and Madsen, C and McLaughlin, J and Nguyen, T and Roehner, N and Bartley, B and Bhatia, S and Bissell, M and Clancy, K and Gorochowski, T and Grunberg, R and Luna, A and Le, Novere N and Pocock, M and Sauro, H and Sexton, J and Stan, G and Tabor, J and Voigt, C and Zundel, Z and Myers, C and Beal, J and Wipat, A},
doi = {10.1515/jib-2017-0074},
journal = {Journal of Integrative Bioinformatics},
title = {Synthetic Biology Open Language Visual (SBOL Visual) Version 2.0},
url = {http://dx.doi.org/10.1515/jib-2017-0074},
volume = {15},
year = {2018}
}
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RIS format (EndNote, RefMan)

TY  - JOUR
AB  - People who are engineering biological organisms often find it useful to communicate in diagrams, both about the structure of the nucleic acid sequences that they are engineering and about the functional relationships between sequence features and other molecular species. Some typical practices and conventions have begun to emerge for such diagrams. The Synthetic Biology Open Language Visual (SBOL Visual) has been developed as a standard for organizing and systematizing such conventions in order to produce a coherent language for expressing the structure and function of genetic designs. This document details version 2.0 of SBOL Visual, which builds on the prior SBOL Visual 1.0 standard by expanding diagram syntax to include functional interactions and molecular species, making the relationship between diagrams and the SBOL data model explicit, supporting families of symbol variants, clarifying a number of requirements and best practices, and significantly expanding the collection of diagram glyphs.
AU  - Cox,R
AU  - Madsen,C
AU  - McLaughlin,J
AU  - Nguyen,T
AU  - Roehner,N
AU  - Bartley,B
AU  - Bhatia,S
AU  - Bissell,M
AU  - Clancy,K
AU  - Gorochowski,T
AU  - Grunberg,R
AU  - Luna,A
AU  - Le,Novere N
AU  - Pocock,M
AU  - Sauro,H
AU  - Sexton,J
AU  - Stan,G
AU  - Tabor,J
AU  - Voigt,C
AU  - Zundel,Z
AU  - Myers,C
AU  - Beal,J
AU  - Wipat,A
DO  - 10.1515/jib-2017-0074
PY  - 2018///
SN  - 1613-4516
TI  - Synthetic Biology Open Language Visual (SBOL Visual) Version 2.0
T2  - Journal of Integrative Bioinformatics
UR  - http://dx.doi.org/10.1515/jib-2017-0074
UR  - http://hdl.handle.net/10044/1/56717
VL  - 15
ER  -
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