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{Misirli:2017:10.1049/enb.2017.0001,
author = {Misirli, G and Madsen, C and Sainz, de Murieta I and Bultelle, M and Flanagan, K and Pocock, M and Halllinan, J and McLaughlin, J and Clark-Casey, J and Lyne, M and Micklem, G and Stan, G and Kitney, R and Wipat, A},
doi = {10.1049/enb.2017.0001},
journal = {Engineering Biology},
pages = {61--65},
title = {Constructing synthetic biology workflows in the cloud},
url = {http://dx.doi.org/10.1049/enb.2017.0001},
volume = {1},
year = {2017}
}
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RIS format (EndNote, RefMan)

TY  - JOUR
AB  - The synthetic biology design process has traditionally been heavily dependent upon manual searching, acquisition and integration of existing biological data. A large amount of such data is already available from Internet-based resources, but data exchange between these resources is often undertaken manually. Automating the communication between different resources can be done by the generation of computational workflows to achieve complex tasks that cannot be carried out easily or efficiently by a single resource. Computational workflows involve the passage of data from one resource, or process, to another in a distributed computing environment. In a typical bioinformatics workflow, the predefined order in which processes are invoked in a synchronous fashion and are described in a workflow definition document. However, in synthetic biology the diversity of resources and manufacturing tasks required favour a more flexible model for process execution. Here, the authors present the Protocol for Linking External Nodes (POLEN), a Cloud-based system that facilitates synthetic biology design workflows that operate asynchronously. Messages are used to notify POLEN resources of events in real time, and to log historical events such as the availability of new data, enabling networks of cooperation. POLEN can be used to coordinate the integration of different synthetic biology resources, to ensure consistency of information across distributed repositories through added support for data standards, and ultimately to facilitate the synthetic biology life cycle for designing and implementing biological systems.
AU  - Misirli,G
AU  - Madsen,C
AU  - Sainz,de Murieta I
AU  - Bultelle,M
AU  - Flanagan,K
AU  - Pocock,M
AU  - Halllinan,J
AU  - McLaughlin,J
AU  - Clark-Casey,J
AU  - Lyne,M
AU  - Micklem,G
AU  - Stan,G
AU  - Kitney,R
AU  - Wipat,A
DO  - 10.1049/enb.2017.0001
EP  - 65
PY  - 2017///
SN  - 2398-6182
SP  - 61
TI  - Constructing synthetic biology workflows in the cloud
T2  - Engineering Biology
UR  - http://dx.doi.org/10.1049/enb.2017.0001
UR  - http://hdl.handle.net/10044/1/49142
VL  - 1
ER  -
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