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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{Yuan:2013:10.1016/j.automatica.2013.02.015,
author = {Yuan, Y and Stan, G-B and Shi, L and Barahona, M and Goncalves, J},
doi = {10.1016/j.automatica.2013.02.015},
journal = {AUTOMATICA},
pages = {1227--1235},
title = {Decentralised minimum-time consensus},
url = {http://dx.doi.org/10.1016/j.automatica.2013.02.015},
volume = {49},
year = {2013}
}

RIS format (EndNote, RefMan)

TY  - JOUR
AU - Yuan,Y
AU - Stan,G-B
AU - Shi,L
AU - Barahona,M
AU - Goncalves,J
DO - 10.1016/j.automatica.2013.02.015
EP - 1235
PY - 2013///
SN - 0005-1098
SP - 1227
TI - Decentralised minimum-time consensus
T2 - AUTOMATICA
UR - http://dx.doi.org/10.1016/j.automatica.2013.02.015
UR - http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000319096300013&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=1ba7043ffcc86c417c072aa74d649202
VL - 49
ER -