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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

@inproceedings{Giannari:2018,
author = {Giannari, AG and van, Logtestijn MDA and Christodoulides, P and Konishi, K and Tanaka, RJ},
pages = {2387--2392},
publisher = {IEEE},
title = {Model Predictive Control for Designing Proactive Therapy of Atopic Dermatitis},
url = {http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000467725302069&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=1ba7043ffcc86c417c072aa74d649202},
year = {2018}
}

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RIS format (EndNote, RefMan)

TY  - CPAPER
AU  - Giannari,AG
AU  - van,Logtestijn MDA
AU  - Christodoulides,P
AU  - Konishi,K
AU  - Tanaka,RJ
EP  - 2392
PB  - IEEE
PY  - 2018///
SP  - 2387
TI  - Model Predictive Control for Designing Proactive Therapy of Atopic Dermatitis
UR  - http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000467725302069&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=1ba7043ffcc86c417c072aa74d649202
ER  -

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