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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{Zhang:2008:10.1109/MCAS.2008.928446,
author = {Zhang, H-T and Chen, MZ and Stan, G-B and Zhou, T and Maciejowski, JM},
doi = {10.1109/MCAS.2008.928446},
journal = {IEEE CIRCUITS AND SYSTEMS MAGAZINE},
pages = {67--85},
title = {Collective Behavior Coordination with Predictive Mechanisms},
url = {http://dx.doi.org/10.1109/MCAS.2008.928446},
volume = {8},
year = {2008}
}

RIS format (EndNote, RefMan)

TY  - JOUR
AU - Zhang,H-T
AU - Chen,MZ
AU - Stan,G-B
AU - Zhou,T
AU - Maciejowski,JM
DO - 10.1109/MCAS.2008.928446
EP - 85
PY - 2008///
SN - 1531-636X
SP - 67
TI - Collective Behavior Coordination with Predictive Mechanisms
T2 - IEEE CIRCUITS AND SYSTEMS MAGAZINE
UR - http://dx.doi.org/10.1109/MCAS.2008.928446
UR - http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000270432500006&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=1ba7043ffcc86c417c072aa74d649202
VL - 8
ER -